Systems and methods for monitoring neural activity

ABSTRACT

Systems and Methods for Monitoring Neural Activity A method of monitoring neural activity responsive to a stimulus in a brain or a subject under general anaesthetic, the method comprising: applying the stimulus to one or more of at least one electrode implanted in a target neural structure of the brain; detecting a resonant response from the target neural structure evoked by the stimulus at one or more of the at least one electrode in or near the target neural structure of the brain; and determining one or more waveform characteristics of the detected resonant response.

TECHNICAL FIELD

The present disclosure relates to deep brain stimulation (DBS) and, inparticular, methods and systems of monitoring neural activity responsiveto DBS.

BACKGROUND

Deep brain stimulation (DBS) is an established therapy for movementdisorders as well as other neurological disorders, including epilepsy,obsessive compulsive disorder, and depression. DBS is typicallyadministered to patients whose symptoms cannot be adequately controlledby medication alone. DBS involves surgically implanting electrodes in ornear to specific neural structures of the brain, typically in thesubthalamic nucleus (STN), the globus pallidus interna (GPi), and/or thethalamus. Electrodes are connected to a neurostimulator usuallyimplanted within the body and configured to deliver electrical pulsesinto target areas. It is believed that this electrical stimulationdisrupts abnormal brain activity causally linked to a patient'ssymptoms. Stimulation parameters can be adjusted using a controllerexternal to the body, remotely connected to the neurostimulator.

Whilst established DBS technology has proven to be effective inalleviating movement disorder symptoms, there are several limitations tostate of the art devices. In particular, established techniques forintraoperative testing of DBS electrodes to ensure correct positioningin the brain, such as x-ray imaging, microelectrode recordings, andclinical assessment can be inaccurate. Consequently, electrodes areoften implanted in suboptimal locations, resulting in diminishedtherapeutic outcomes and unwanted side-effects. After implantation, DBSdevices require manual adjustment by a clinician. This typicallyinvolves the clinician adjusting parameters of the stimulus based on alargely subjective assessment of immediate or short-term improvement ofthe patient's symptoms. Since therapeutic effects can be slow to emergeand because the DBS parameter space is large, the task of finding apreferred set of parameters is time- and cost-inefficient, and can leadto suboptimal therapeutic outcomes. In addition, the constant,non-varying application of electrical stimulation using conventional DBScan also lead to suboptimal therapeutic outcomes, including unwantedside effects, as well as reduced battery life of DBS stimulators.

SUMMARY

According to a first aspect of the disclosure, there is provided amethod of monitoring neural activity responsive to a stimulus in a brainof a subject, the method comprising: inducing general anaesthesia in thesubject; applying the stimulus to one or more of at least one electrodeimplanted in the brain; detecting a resonant response from the targetneural structure evoked by the stimulus at one or more of the at leastone electrode in or near a target neural structure of the brain; anddetermining one or more waveform characteristics of the detectedresonant response.

According to another aspect of the disclosure, there is provided amethod of monitoring neural activity responsive to a stimulus in a brainof a subject under general anaesthetic, the method comprising: inducinggeneral anaesthesia in the subject; applying the stimulus to one or moreof at least one electrode implanted in the brain; detecting a resonantresponse from the target neural structure evoked by the stimulus at oneor more of the at least one electrode in or near a target neuralstructure of the brain; and determining one or more waveformcharacteristics of the detected resonant response.

The one or more waveform characteristics may be determined based on atleast part of a second or subsequent cycle in the detected resonantresponse.

The one or more waveform characteristics may comprise one or more of thefollowing: a) a frequency of the resonant response; b) a temporalenvelope of the resonant response; c) an amplitude of the resonantresponse; d) a fine structure of the resonant response; e) a rate ofdecay of the resonant response; f) a delay between the onset of thestimulus and the onset of a temporal feature of the resonant response.

The stimulus may comprise a plurality of pulses.

The step of determining the one or more waveform characteristics maycomprise comparing a first characteristic over two or more cycles of thedetected resonant response. The step of determining the one or morewaveform characteristics may comprise determining a change of the firstcharacteristic over the two or more cycles. The step of determining theone or more waveform characteristics may comprise determining a rate ofchange of the first characteristic over the two or more cycles.

The resonant response may comprise a plurality of resonant components.One or more of the plurality of resonant components from a neuralstructure different from the target neural structure.

The method may further comprise adjusting the location of one or more ofthe at least one electrodes based on the one or more determined waveformcharacteristics.

The method may further comprise adapting the stimulus based on the oneor more determined waveform characteristics of the resonant response.The adapting may comprise adjusting one or more of the frequency,amplitude, pulse-width, electrode configuration, or morphology of thestimulus.

The method may further comprise correlating the detected resonantresponse with a template resonant response; and adapting the stimulusbased on the correlation. The method may further comprise correlatingthe one or more determined waveform characteristics with one or morepredetermined threshold values; and adapting the stimulus based on thecorrelation.

The stimulus may be non-therapeutic or therapeutic.

The stimulus may comprise a patterned signal comprising a plurality ofbursts separated by a first time period, each burst comprising aplurality of pulses separated by a second time period, wherein the firsttime period is greater than the second time period and wherein thedetecting is performed during one or more of the first time periods. Thefirst time period may be greater than or equal to the second timeperiod. The plurality of pulses within at least one of the bursts mayhave different amplitudes. The different amplitudes may be selected toproduce a ramp in amplitude of sequential pulses in the at least one ofthe bursts. The final pulse in each of the plurality of bursts may besubstantially identical.

The method may further comprise: estimating a patient state of a patientbased on the determined one or more waveform characteristics. In whichcase, the method may further comprise diagnosing the patient based onthe estimate of the patient's state and/or generating one or more alertsassociated with the estimated patient state; and outputting the one ormore alerts.

The method may further comprise applying a second stimulus to a targetneural structure in the brain; detecting a second resonant response fromthe target neural structure evoked by the second stimulus at one or moreof the at least one electrode implanted in or near the target neuralstructure; determining one or more second waveform characteristics ofthe detected second resonant response.

The method may further comprise: estimating a degree of progression of adisease associated with the patient based on the one or more firstwaveform characteristics and the one or more second waveformcharacteristics.

The method may further comprise: determining the effect of a therapyprovided to the patient based on the one or more first waveformcharacteristics and the one or more second waveform characteristics. Thetherapy may be medication or deep brain stimulation.

The at least one electrode may comprise two or more electrodes locatedwithin different neural structures in the brain. The at least oneelectrode may comprise two or more electrodes located within differenthemispheres of the brain.

The method may further comprise: determining whether one or more of theat least one electrode is positioned in the target neural network basedon the detected resonant response. The method may further comprisemoving one or more of the first electrode and the second electrode basedon the detected resonant response.

The steps of applying the stimulus, detecting a resonant response anddetermining one or more waveform characteristics of the detectedresonant response, may be repeated one or more times so that a series ofresonant responses are detected, each in response to application of aseparate signal. These steps may be repeated until it is determined thatone or more of the at least one electrode is positioned in the targetneural structure.

The method may further comprise comparing a common waveformcharacteristic between two or more detected resonant responses.

The method may further comprise comparing a degree of change of a commoncharacteristic between two or more detected resonant responses.

The method may further comprise determining a rate of change of a commoncharacteristic between two or more detected resonant responses.

The method may further comprise selecting one or more of the at leastone electrode to use for therapeutic stimulation of the target neuralstructure based on the one or more waveform characteristics; andapplying a therapeutic stimulus to the target neural structure via theselected one or more of the at least one electrode.

The method may further comprise: inserting the at least one electrodeinto the brain along a predefined trajectory; wherein steps of applyingthe stimulus, detecting a resonant response and determining one or morewaveform characteristics of the detected resonant response are repeatedwhile the at least one electrode is being inserted to generate a profileof resonant responses with respect to the predefined trajectory and thetarget neural structure.

The profile of resonant responses may be used to determine a position ofthe one or more electrodes relative to the target neural structure.

The at least one electrode may comprises a plurality of electrodes, andthe steps of applying the stimulus, detecting a resonant response anddetermining one or more waveform characteristics of the detectedresonant response may be repeated using different combinations of the atleast one electrode to generate a profile of resonant responses.

The method may further comprise: selecting one or more of the at leastone electrode based on the profile of neural responses; and applying atherapeutic stimulus to the selected one or more of the at least oneelectrode. The selected one or more of the at least one electrode maycomprise a plurality of electrodes.

The one or more of the at least one electrode used to apply the stimulusmay comprise at least two electrodes. Equally, the one or more of the atleast one electrode used to detect the resonant response may comprise atleast two electrodes.

The neural target structure may be part of the cortico-basalganglia-thalamocortical circuit.

The neural target structure may be the subthalamic nucleus, globuspallidus interna, substantia nigra pars reticulata, pedunculopontinenucleus.

According to another aspect of the disclosure, there is provided aneurostimulation system, comprising: a lead having at least oneelectrode adapted for implantation in or near a target neural structurein the brain; a signal generator selectively coupled to one or more ofthe at least one electrode and configured to generate a stimulus tostimulate the target neural structure; a measurement device selectivelycoupled to one or more of the at least one electrode and configured todetect a resonant response from the target neural structure evoked bythe stimulus; a processing unit coupled to the measurement device andconfigured to determine one or more waveform characteristics of thedetected resonant response.

The one or more waveform characteristics may be determined based on atleast part of a second or subsequent cycle in the detected resonantresponse.

The one or more waveform characteristics comprises one or more of thefollowing: a) a frequency of the resonant response; b) a temporalenvelope of the resonant response; c) an amplitude of the resonantresponse; d) a fine structure of the resonant response; e) a rate ofdecay of the resonant response; f) a delay between the onset of thestimulus and the onset of a temporal feature of the resonant response.

The stimulus may comprise a plurality of pulses.

In determining the one or more waveform characteristics, the processingunit may be configured to correlate a first characteristic over two ormore cycles of the detected resonant response.

In determining the one or more waveform characteristics, the processingunit may be configured to determine a degree of change of the firstcharacteristic over the two or more cycles.

In determining the one or more waveform characteristics, the processingunit may be configured to determine a rate of change of the firstcharacteristic over the two or more cycles.

The resonant response may be detected at a different one or moreelectrodes to the one or more electrodes at which the stimulus isapplied.

The resonant response may comprise a plurality of resonant components.

The processing unit may be coupled to the signal generator andconfigured to selectively control the output of the signal generator.

The processing unit may be configured to: control the signal generatorto adapt the stimulus based on the one or more determined waveformcharacteristics of the resonant response.

The processing unit may be further configured to: correlate the detectedresonant response with a template resonant response; and control thesignal generator to adapt the stimulus based on the correlation.

The processing unit may be configured to: correlate the one or moredetermined waveform characteristics with one or more predeterminedthreshold values; and control the signal generator to adapt the stimulusbased on the correlation.

The adapting may comprise adjusting one or more of the frequency,amplitude, pulse-width, electrode configuration, or morphology of thestimulus.

The stimulus may be non-therapeutic or therapeutic.

The stimulus may comprise a patterned signal comprising a plurality ofbursts separated by a first time period, each burst comprising aplurality of pulses separated by a second time period, wherein the firsttime period is greater than the second time period and wherein thedetecting is performed during one or more of the first time periods. Thefirst time period is greater than or equal to the second time period.The plurality of pulses within at least one of the bursts may havedifferent amplitudes.

The different amplitudes may be selected to produce a ramp in amplitudeof sequential pulses in the at least one of the bursts.

The final pulse in each of the plurality of bursts is preferablysubstantially identical.

The processing unit may be configured to: estimate a patient state of apatient based on the determined one or more waveform characteristics.

The processing unit may be configured to: diagnosing the patient basedon the estimate of the patient's state.

The processing unit may be configured to: generating one or more alertsassociated with the estimated patient state; and output the one or morealerts.

The processing unit may be configured to: estimate a degree ofprogression of a disease associated with the patient or an effect of atherapy provided to the patient based on the one or more waveformcharacteristics and one or more second waveform characteristics, the oneor more second waveform characteristics determined based on a secondresonant response detected after the resonant response.

The therapy may be medication or deep brain stimulation.

The system may further comprise: a second lead having at least onesecond electrode adapted for implantation in or near a second targetstructure in the brain; wherein the signal generator is selectivelycoupled to one or more of the at least one second electrode andconfigured to generate a stimulus to stimulate the second target neuralstructure; wherein the measurement device is selectively coupled to oneor more of the at least one second electrode and configured to detect aresonant response from the second target neural structure evoked by thestimulus; a processing unit coupled to the measurement device andconfigured to determine one or more waveform characteristics of thedetected resonant response from the second target neural structure.

The lead and the second lead may be located within or near to differentneural structures in the brain. The lead and the second lead may belocated within different hemispheres of the brain.

The processing unit may be configured to: determine whether one or moreof the at least one electrode is positioned in the target neural networkbased on the detected resonant response.

The signal generator, the measurement device and the processing unit aremay be configured to repeat the steps of applying the stimulus,detecting a resonant response and determining one or more waveformcharacteristics of the detected resonant response. In which case, thesteps of applying the stimulus, detecting a resonant response anddetermining one or more waveform characteristics of the detectedresonant response may be repeated until processing unit determines thatone or more of the at least one electrode is positioned in the targetneural structure.

The processing unit may be configured to control the signal generatorto: select one or more of the at least one electrode to use fortherapeutic stimulation of the target neural structure based on the oneor more waveform characteristics; and apply a therapeutic stimulus tothe target neural structure via the selected one or more of the at leastone electrode.

The steps of applying the stimulus, detecting a resonant response anddetermining one or more waveform characteristics of the detectedresonant response may be repeated while the at least one electrode isbeing inserted; and the processing unit may be further configured togenerate a profile of resonant responses with respect to the predefinedtrajectory and the target neural structure.

The processing unit may be configured to determine a position of the oneor more electrodes relative to the target neural structure based on theprofile of resonant responses.

The at least one electrode may comprise a plurality of electrodes. Inwhich case, the steps of applying the stimulus, detecting a resonantresponse and determining one or more waveform characteristics of thedetected resonant response may be repeated using different combinationsof the at least one electrode to generate a profile of resonantresponses.

The processing unit may be configured to: select one or more of the atleast one electrode based on the profile of neural responses; andcontrol the signal generator to applying a therapeutic stimulus to theselected one or more of the at least one electrode.

The selected one or more of the at least one electrode may comprise aplurality of electrodes.

The one or more of the at least one electrode used to apply the stimulusmay comprise at least two electrodes and/or wherein the one or more ofthe at least one electrode used to detect the resonant responsecomprises at least two electrodes.

The neural target structure may be part of the cortico-basalganglia-thalamocortical circuit.

The neural target structure may be the subthalamic nucleus, globuspallidus interna, substantia nigra pars reticulata, pedunculopontinenucleus.

According to another aspect of the disclosure, there is provided amethod of monitoring neural activity in a brain of a subject responsiveto a stimulus, the method comprising:

a. inducing general anaesthesia in the subject;

b. applying the stimulus to a target neural structure in the brain; and

c. detecting a neural response evoked by the stimulus at an electrodeimplanted in or near the target neural structure,

wherein the stimulus comprises a patterned signal comprising a pluralityof bursts separated by a first time period, each burst comprising aplurality of pulses separated by a second time period, wherein the firsttime period is greater than the second time period and wherein thedetecting is performed during one or more of the first time periods.

According to another aspect of the disclosure, there is provided amethod of monitoring neural activity in a brain of a subject undergeneral anaesthetic responsive to a stimulus, the method comprising:

a. applying the stimulus to a target neural structure in the brain; and

b. detecting a neural response evoked by the stimulus at an electrodeimplanted in or near the target neural structure,

wherein the stimulus comprises a patterned signal comprising a pluralityof bursts separated by a first time period, each burst comprising aplurality of pulses separated by a second time period, wherein the firsttime period is greater than the second time period and wherein thedetecting is performed during one or more of the first time periods.

The first time period is preferably greater than or equal to the secondtime period.

The stimulus is preferably biphasic. The plurality of pulses within aburst may have different amplitudes. The different amplitudes may beselected to produce a ramp. The final pulse in each of the plurality ofbursts may be substantially identical. The stimulus may be patterned tobe non-therapeutic or therapeutic.

In any of the aspects described above, general anaesthesia in thesubject may be induced using an agent selected from propofol, sodiumthiopental, etomidate, methohexital, ketamine, and sevoflurane.

In any of the aspects described above, general anaesthesia in thesubject may be maintained using an agent selected from isoflurane,sevoflurane, desflurane, methoxyflurane, halothane, nitrous oxide, andxenon.

In any of the aspects described above, general anaesthesia in thesubject may be maintained using fentanyl, a fentanyl derivative, abarbiturate, or benzodiazepines.

In any of the aspects described above, general anaesthesia in thesubject may be maintained using fentanyl, remifentanyl or a fentanylderivative.

In any of the aspects described above, general anaesthesia in thesubject may be induced using propofol and maintained using a combinationof sevoflurane and remifentanyl.

BRIEF DESCRIPTION OF DRAWINGS

Embodiments of the present disclosure will now be described by way ofnon-limiting examples with reference to the drawings, in which:

FIG. 1 is a graph illustrating resonance from a neural structureresponsive to a deep brain stimulation (DBS) signal;

FIG. 2 is a graph illustrating resonance from a neural structureresponsive to a patterned DBS signal;

FIG. 3 is a graph illustrating evoked resonance responsive to 10consecutive pulses of a DBS signal;

FIG. 4 is a graph illustrating the range and variance of peak amplitudeof a resonant response to continuous and patterned DBS;

FIG. 5a is a graphical illustration showing neural resonance evoked by acontinuous non-therapeutic patterned DBS signal;

FIG. 5b is a graphical illustration showing neural resonance evoked by acontinuous therapeutic patterned DBS signal;

FIG. 5c is a graphical illustration showing neural resonance after atransition from a continuous therapeutic DBS signal to a non-therapeuticDBS signal;

FIG. 5d is a graph illustrating the estimated frequency of evokedresonance responsive to a non-therapeutic DBS signal;

FIG. 5e is a graph illustrating the estimated frequency of evokedresonance responsive to a therapeutic DBS signal;

FIG. 5f is a graph illustrating the estimated frequency of evokedresonance responsive to a transition between a therapeutic DBS signaland a non-therapeutic DBS signal;

FIG. 6a is a graphical illustration showing neural resonance evoked by acontinuous non-therapeutic patterned DBS signal;

FIG. 6b is a graphical illustration showing neural resonance evoked by acontinuous therapeutic patterned DBS signal;

FIG. 6c is a graphical illustration showing neural resonance after atransition from a continuous therapeutic DBS signal to a non-therapeuticDBS signal;

FIG. 6d is a graph illustrating the estimated frequency of evokedresonance responsive to a non-therapeutic DBS signal;

FIG. 6e is a graph illustrating the estimated frequency of evokedresonance responsive to a therapeutic DBS signal;

FIG. 6f is a graph illustrating the estimated frequency of evokedresonance responsive to a transition between a therapeutic DBS signaland a non-therapeutic DBS signal;

FIG. 7a is a graph illustrating evoked resonances beginning to divergeinto two peaks in response to patterned DBS with an amplitude of 1.5 mA;

FIG. 7b is a graph illustrating evoked resonances diverging into twopeaks in response to patterned DBS with an amplitude of 2.25 mA;

FIG. 7c is a graph illustrating two separate evoked resonant peaks inresponse to patterned DBS with an amplitude of 3.375 mA;

FIG. 8 is a schematic illustration of an electrode lead tip forimplantation in a brain;

FIG. 9 is a schematic illustration of an electrode lead implanted in thesubthalamic nucleus of a brain;

FIG. 10 is a schematic illustration of a system for administering DBS;

FIG. 11 is a flow diagram illustrating a process for locating a DBSelectrode in the brain;

FIG. 12 is a flow diagram illustrating a process for monitoring andprocessing resonant responses at multiple electrodes in response tostimulation at multiple electrodes;

FIG. 13 is a graphical illustration of resonant responses measured atdifferent electrodes implanted in a brain responsive to a stimulationsignal in accordance with the process shown in FIG. 12;

FIG. 14 is a graphical illustration of resonant responses measured atdifferent electrodes implanted in a brain responsive to stimulationsignals applied at different electrodes in accordance with the processshown in FIG. 12;

FIG. 15 is a flow diagram illustrating a process for determiningparameters for a DBS stimulation signal based on medicating the patient;

FIG. 16 is a flow diagram illustrating a process for generating astimulation signal with closed-loop feedback based on evoked resonanceat a target neural structure;

FIG. 17 is a flow diagram illustrating another process for generating astimulation signal with closed-loop feedback based on evoked resonanceat a target neural structure;

FIG. 18 graphically illustrates switching between periods of therapeuticand non-therapeutic stimulation relative to a resonant activity featureof an evoked response in accordance with the process of FIG. 17;

FIG. 19a illustrates a patterned stimulation signal according to anembodiment of the present disclosure;

FIG. 19b illustrates another patterned stimulation signal according toan embodiment of the present disclosure

FIG. 20 illustrates the results of movement function tests for patientsreceiving DBS;

FIGS. 21a to 21g are graphical illustration showing neural resonanceevoked by a continuous therapeutic patterned DBS signal;

FIG. 22 is a three-dimensional reconstructions of an electrode arrayimplanted in a STN (smaller mass) and subantia nigra .(larger mass) of apatient;

FIG. 23 is a merged MRI and CT scan of a patient's brain showing thepositioning of an electrode array;

FIG. 24 graphically illustrates the variation in ERNA amplitude relativeto electrode position;

FIG. 25A graphically illustrates ERNA frequency vs DBS amplitude for 19brain hemispheres;

FIG. 25B graphically illustrates ERNA amplitude vs DBS amplitude for 19brain hemispheres;

FIG. 25C graphically illustrates Relative beta(RMS_(13-30 Hz)/RMS_(4-45 Hz)) vs DBS amplitude for 19 brainhemispheres;

FIG. 25D graphically illustrates Relative beta correlated with ERNAfrequency (Σ=0.601, p<0.001) for 19 brain hemispheres;

FIG. 26A graphically illustrates ERNA frequency washout over consecutive15 s periods post-DBS and in the last 15 s pre-DBS for 19 brainhemispheres;

FIG. 26B graphically illustrates ERNA amplitude washout for 19 brainhemispheres;

FIG. 26C graphically illustrates Relative beta washout for 19 brainhemispheres; and

FIG. 26D graphically illustrates Washout in the 200-400 Hz HFO band for19 brain hemispheres

FIG. 27 is a graphical illustration of ERNA in the brain of a patientboth awake and under general anaesthetic responsive to DBS stimulation;

FIG. 28 is a graph showing the variation of ERNA in a patient acrossfour electrodes of an electrode array at implantation (awake) and 560days later under general anaesthetic;

FIG. 29 is a graphical illustration of ERNA measured at differentelectrodes implanted in the left STN of a brain of a patient undergeneral anaesthetic responsive to stimulation signals applied atdifferent electrodes;

FIG. 30 is a graphical illustration of ERNA measured at differentelectrodes implanted in the right STN of a brain of a patient undergeneral anaesthetic responsive to stimulation signals applied atdifferent electrodes;

FIG. 31 is a graphical illustration of ERNA measured at differentelectrodes implanted in the left STN of a brain of a patient undergeneral anaesthetic responsive to stimulation signals applied atdifferent electrodes;

FIG. 32 is a graphical illustration of ERNA measured at differentelectrodes implanted in the right STN of a brain of a patient undergeneral anaesthetic responsive to stimulation signals applied atdifferent electrodes;

FIG. 33 is a graphical illustration of ERNA measured at differentelectrodes implanted in the left STN of a brain of a patient undergeneral anaesthetic responsive to stimulation signals applied atdifferent electrodes;

FIG. 34 is a plot showing range, median and interquartile range of ERNAamplitude measured at different electrodes implanted in the STNs ofbrains of patients awake and under general anaesthetic responsive tostimulation signals applied at different electrodes;

FIGS. 35A to 35B are rank plots showing correlations between ERNAamplitude measured at electrodes implanted in the STNs of brains ofpatients awake and under general anaesthetic responsive to stimulationsignals applied at different electrodes;

FIG. 36 is a graphical illustration of ERNA measured at a singleelectrode implanted in the STN of a brain of a patient under generalanaesthetic responsive to a stimulation signal;

FIGS. 37a and 37b are plots showing range, median and interquartilerange of ERNA peak-to-peak latency measured at electrodes implanted in36 STNs of brains of patients awake and under general anaestheticinduced by propofol and sevoflurane responsive to stimulation signalsapplied at different electrodes;

FIGS. 38 to 40 are graphical illustrations of ERNA measured in the STNof a brain of a sheep under general anaesthetic responsive tostimulation signals applied at different electrodes at 3.375 mA, 5.063mA and 7.594 mA respectively;

FIGS. 41 to 43 are graphical illustrations of ERNA measured in the STNof a brain of a sheep under general anaesthetic responsive tostimulation signals applied at different electrodes at 3.375 mA, 5.063mA and 7.594 mA respectively.

DESCRIPTION OF EMBODIMENTS

Embodiments of the present disclosure relate to improvements inneuro-stimulation in the brain. DBS devices typically apply a constantamplitude stimulus to a target area of the brain at a constant frequencyof 130 Hz. The inventors have determined not only that application ofsuch a stimulus evokes a neural response from the target area of thebrain, but that the neural response comprises a resonant component whichhas not previously been recognized. Continuous DBS at conventionalfrequencies does not allow a long enough time window to observe theresonant activity. However, by monitoring the neural response afterstimulation has ceased (by patterning the stimulation signal orotherwise), the resonant activity can be monitored. In addition, theinventors have realized that embodiments of the present invention haveapplications both for reducing the physical effects associated withmotor diseases, and also the detrimental effects of other neurologicalconditions, neuropsychiatric disorders, sensory disorders, and pain.

In addition to the above, the inventors have also realized that neuronaloscillations, as reflected in local field potentials measured, forexample, via implanted electrodes, by EEG, or by MEG, are also affectedboth by DBS and certain medications used to treat movement disorders. Inparticular, high frequency oscillations (HFOs) in the range of 200 to400 Hz, measured in local field potentials by DBS electrodes implantedin the subthalamic nucleus (STN) of the brain, have been found to bemodulated both by DBS and with the use of medication, such as levodopa.This realization has led the inventors to develop novel techniques ofselecting optimal DBS treatment parameters based on measured HFOmodulation. FIG. 1 graphically illustrates a response from a neuralcircuit stimulated by a 130 Hz signal delivered from a neurostimulatorvia an electrode lead, such as the 3387 electrode lead manufactured byMedtronic (RTM), implanted in the subthalamic nucleus (STN) of aParkinson's disease (PD) patient. Each response to a stimulus pulsecomprises an evoked compound action potential (ECAP) component togetherwith a component of evoked resonant neural activity (ERNA) occurringafter the ECAP. The ECAP typically occurs within 1-2 milliseconds of thestimulus pulse. The graph shows the response to the last threeconsecutive pulses of a 60 second period of continuous stimulationfollowed by a period of no stimulation. It can be seen that the evokedresonant response to each of the first two stimulus pulses shown in FIG.1 is cut short by the onset of the next stimulus pulse, such that only asingle secondary peak is detected. However, the evoked resonant responseto the third (and final) pulse is able to resonate for longer and so canbe clearly seen in the form of a decaying oscillation with at leastseven peaks for a post-stimulus period of about 30 milliseconds.

As mentioned above, it is known for clinicians to control and adjust DBSparameters to elicit therapeutic effects in a patient. The inventorshave realized that by controlling the DBS parameters in certain ways, anon-therapeutic stimulus can be administered which evokes a resonantneural response (ERNA) in a patient without having any therapeuticimpact or causing undesirable side effects. Such non-therapeutic stimulican be used to reliably measure ERNA without causing sustained changesto the resonant neural circuit or the patient's symptomatic state.Non-therapeutic stimulation is preferably achieved by administering astimulus comprising a short burst of pulses followed by a period of nostimulation, and the ERNA is measured during this period of nostimulation. By doing so, the total charge or energy provided to thepatient is below a therapeutic threshold, and the measured ERNA providesinformation concerning the patient's natural state (without therapy). Inan alternative embodiment, the overall charge or energy provided to thepatient may be reduced by reducing the amplitude of the stimulationsignal below a therapeutic threshold. However, doing so may also reducethe amplitude of peaks in the ERNA making it more difficult to observe.

In addition to the above, the inventors have determined that patternedstimulation can be used to monitor and analyze evoked resonant neuralactivity during therapeutic stimulation of a patient. By patterning thestimulation signal, therapeutic stimulation can be maintained whilstproviding time windows in which to monitor resonant responses past thatof the first resonant peak or more preferably past two or more resonantpeaks.

FIG. 2 graphically illustrates an example therapeutic patterned DBSstimulus 20 and the associated evoked resonant response according to anembodiment of the present disclosure. The patterned stimulus 20 is shownabove the graph to illustrate the correlation between stimulus andresponse. In the patterned stimulus, a single pulse has been omittedfrom an otherwise continuous 130 Hz pulse train. The pulse traintherefore includes a plurality of bursts of pulses of continuousstimulation, each burst separated by a first time period t₁, each of theplurality of pulses separated by a second time period t₂. Continuationof the stimulus before and after omission of a pulse (or more than onepulse) maintains the therapeutic nature of the DBS, whilst the omissionof a pulse allows for resonance of the ERNA to be monitored over several(3 in this example) resonant cycles before the next stimulation pulseinterrupts this resonance.

In summary, by patterning non-therapeutic and therapeutic stimuli, anevoked response can be monitored over a longer period of time than withconventional non-patterned stimulation. Accordingly, stimuli arepreferably applied in bursts of multiple pulses, each burst separated bya first time period t₁ of no stimulation, each pulse separated by asecond time period t₂. For example, a stimulus signal may comprise aseries of 10-pulse bursts at 130 Hz. To increase repeatability ofresults, the multi-pulse burst may be repeated after a predeterminedperiod of no stimulation. For example, the multi-pulse burst may berepeated each second. The duration of the first time period t₁ isgreater than that of the second time period t₂. The ratio between theduration of the burst and the duration between bursts may be chosen soas to ensure that relevant properties of the ERNA can be monitoredeasily and efficiently. In some embodiments, the duration of each burstis chosen to be between 1% and 20% of the duration of no stimulationbetween bursts.

In other embodiments, the duration of each burst may be chosen tominimize the effects of stimulation on the measured ERNA or toaccentuate particular features of the measured ERNA. FIG. 3 graphicallyillustrates how the application of 10 pulses at 130 Hz can affect ERNA.The response to the first pulse has a broad, low amplitude first peak.The first peak becomes larger and sharper for subsequent pulses, whilstalso shifting to an earlier time. In some embodiments, the optimumnumber of pulses comprised in a burst may be chosen to maximize theamplitude of the resonance, whilst minimizing the time shift of a peakin ERNA across the burst (e.g., the fourth pulse). In other embodiments,the rate of change in ERNA features (e.g. amplitude, onset delay) acrossconsecutive pulses in a burst may be used as a defining characteristic.For example the rate of change across a burst may be used to determineelectrode position, optimum parameters, patient state, etc. and/or as aclosed loop control signal.

The use of bursts (e.g. 10 pulses) stimulation provides high amplitudeevoked neural responses, making them easier to measure than responses tomore continuous DBS. FIG. 4 graphically illustrates the range andvariance of first peak amplitude of ERNA responsive to more continuousDBS where one pulse is skipped every second (left) and burst DBS (right)(10 pulses only per second). It can be seen that the average peakamplitude of ERNA responsive to burst DBS is around 310 μV whereas theaverage peak amplitude of ERNA responsive to more continuous DBS isaround 140 μV. Further, by using burst stimulation, the evoked resonantresponse over several oscillatory cycles (20 milliseconds or more) canbe monitored.

By analyzing characteristics of the ERNA, the inventors have determinedthat waveform characteristics of the ERNA (natural frequency, dampingfactor, envelope, fine structure, onset delay, rate of change, etc.) aredependent on various physiological conditions of the patient. Forexample, it has been found that therapeutic DBS decreases the frequencyof resonance of the target neural circuit.

Changes in ERNA Related to DBS Stimulation

FIGS. 5a, 5b, and 5c illustrate the variation of frequency of the ERNAduring non-therapeutic stimulation (FIG. 5a ), therapeutic stimulation(FIG. 5b ), and the ERNA after a transition of stimulation fromtherapeutic stimulation to non-therapeutic stimulation (FIG. 5c ).Resonant frequency of the ERNA was measured by calculating the inverseof the time delay between the maxima of two peaks of the ERNA. In otherembodiments, the resonant frequency may be calculated as an inverse ofthe average time delay between maxima of all detected peaks of the ERNA.In further embodiments, the resonant frequency may be calculated byfitting a damped oscillator model to the resonant activity andextracting the natural frequency or by performing spectral analyses(e.g. Fourier transform, wavelet transform). Other techniques forfrequency estimation, such as estimating the time between zero-crossingsin the waveform or using other features of the waveform may also be usedfor this purpose.

In the example shown, a patterned stimulus was administered to thepatient in the same manner as described with reference to FIGS. 1 and 2.FIGS. 5a and 5b show the responses to a patterned non-therapeutic andtherapeutic DBS stimulation, respectively. In this example,non-therapeutic stimulation consisted of bursts of 10 pulses deliveredat a frequency of 130 Hz over a 1-second time period with the remaining120 pulses (which would be present during continuous stimulation)skipped. The typical observable window of the response (duringcontinuous (non-patterned) DBS) is denoted by the horizontal dottedline. It can be seen that with patterned non-therapeutic stimulation,the amplitude and frequency of the ERNA remain relatively constantindicating that the stimulus did not strongly affect the resonant stateof the target neural structure over time. Further, two resonant peaks ofthe ERNA (represented in black) can be seen in the typical observablewindow for non-patterned stimulation. FIG. 5b then shows the responsesto therapeutic patterned DBS stimulation at 3.375 mA where 129 pulsesare delivered per second at a rate of 130 Hz, with the remaining 1 pulseskipped.

The therapeutic signal causes the frequency of the ERNA to reduce, inturn potentially causing the second resonant peak of the ERNA to moveoutside the typical observable window for continuous (non-patterned)stimulation. However by patterning the stimulation by skipping one ormore pulses, it is possible to continue to measure the resonantproperties of the ERNA, along with subsequent peaks during the period inwhich a stimulation pulse is omitted. Additionally, it can be seen thatthe amplitude of the third and fourth resonant peaks are increased incomparison to the non-therapeutic responses.

Alternative methods of patterning the stimulation, rather than merelyomitting pulses in a periodic pulse train, may improve the monitoring ofERNA. For example, conventional, therapeutic stimulation (e.g. at afrequency of 130 Hz) may be interleaved with bursts of stimulationhaving a lower frequency (e.g. 90 Hz). The frequency of theseinterleaving bursts is preferably low enough to allow for multiple ERNApeaks to be observed. Equally, the frequency of these interleavingbursts is preferably high enough to be within the therapeutic frequencyrange for DBS. The transition between frequencies may be abrupt or,alternatively the change in frequency may be gradual. Applying ramps tothe frequency of the pulses to avoid an abrupt step change in frequencymay be advantageous.

Additionally or alternatively to adjusting the frequency of the appliedstimulus, the amplitude of pulses may be modulated over time. This mayinclude applying a ramp to increase the pulse amplitudes over severalpulses within a burst and/or a ramp to decrease the pulse amplitudesover several pulses within a burst. To enhance the monitoring of ERNA itmay be advantageous to apply a fixed amplitude to the pulses precedingthe observation window, and if this amplitude differs from that appliedat other times (e.g. to maximize therapeutic benefit), then applyingramps to the amplitude of the pulses to avoid an abrupt step change inamplitude may be advantageous.

FIG. 5c then shows the responses after switching back to thenon-therapeutic patterned stimulation. In this case the therapeuticeffect of the patterned therapeutic stimulus ‘washes out’ and the ERNAreturns to its baseline state. It can be seen that the first peak ofresonant activity across all conditions (typically all that can bemeasured using conventional continuous DBS) does not vary greatly withtherapeutic DBS. However, characteristics of subsequent parts of theERNA waveform, made measurable by patterning the stimulation, exhibitmuch larger changes in frequency and amplitude. Monitoring of theresponse over a longer period therefore enables information concerningfrequency, amplitude, envelope, and fine structure of the time-varyingoscillation to be analyzed.

This effect is further illustrated by FIGS. 5d, 5e, and 5f . FIG. 5dshows the resonant frequency of the ERNA during periods ofnon-therapeutic stimulation to be around 400-450 Hz. Clinicallyeffective stimulation (stimulation operable to actively reduce apatient's disease symptoms) reduces the frequency of the ERNA to around300-350 Hz as shown in FIG. 5e . FIG. 5f illustrates the transition ofresonant frequency from 300-350 Hz back to around 400-450 Hz aftertherapeutic stimulation has been replaced with non-therapeuticstimulation.

FIGS. 6a, 6b, and 6c illustrate another example from a different patientof the variation of the ERNA during non-therapeutic patternedstimulation (FIG. 6a ), therapeutic patterned stimulation (FIG. 6b ) andthe ERNA after a transition from therapeutic stimulation tonon-therapeutic stimulation (FIG. 6c ). In this example, patternedstimuli were administered to the patient in the same manner as describedwith reference to FIGS. 5a to 5e . As with the previous example, it canbe seen that the initial non-therapeutic stimulation (FIG. 6a ) does notcause noticeable changes to the ERNA and that the therapeuticstimulation (FIG. 6b ) causes a reduction in the frequency of theresonance, which returns to baseline levels after the stimuli istransitioned back to non-therapeutic patterned stimulation (FIG. 6c ).However, in this example, the change in resonant frequency withtherapeutic stimulation is accompanied by an increase in the delaybetween each stimulus pulse and the onset of the resonance. Thisincrease in onset delay shifts the second resonant peak such that itoccurs outside the typical observable window for conventional(non-patterned) DBS. By patterning the stimulation, the measurementwindow is made long enough to observe three resonant peaks, allowingERNA to be characterized. Furthermore, contrary to the previous example,the amplitude of the resonance is decreased by therapeutic stimulation.

FIGS. 6d, 6e, and 6f further illustrate the reduction in resonantfrequency with therapeutic stimulation in this example Resonantfrequency was estimated by calculating the inverse of the time delaybetween the maxima of two peaks of the ERNA. In FIG. 6d , the frequencyof the ERNA measured using non-therapeutic patterned stimulation can beseen to be about 350 Hz. The application of therapeutic patternedstimulation in FIG. 6e causes the frequency to decrease to around 250Hz. The frequency can be seen to be returning to its baseline level inFIG. 6f after transitioning back to non-therapeutic patternedstimulation.

ERNA Comprising Multiple Resonances

The inventors have determined not only that evoked neural responses toapplied stimuli exhibit resonant activity, but that in some instancesevoked activity comprises multiple resonances. FIGS. 7a, 7b and 7cillustrate ERNA in response to continuous DBS at 1.5 mA, 2.25 mA and3.375 mA respectively. At 1.5 mA the resonant ERNA starts as a singlepeak, which can be seen to begin to diverge slightly into two peaks. At2.25 mA, the dominance switches to the later of the two peaks. However,the earlier peak, which was dominant at 1.5 mA, continues at loweramplitude. At 3.375 mA, two peaks are present, with the later peakdominating. It is thought that these multiple resonant peaks correspondto activity in different neural circuits. The relative amplitude betweenthese resonant responses (or other features, such as temporal orspectral properties) may be an indicator of therapeutic state.

ERNA Measurements from Chronically Implanted Electrodes

FIGS. 20 to 23 provide further evidence of the positive effects of DBSon patient symptoms and related changes in ERNA. The data shown in thesefigures was collected from a patient with Parkinson's disease implantedwith an electrode array. The electrode array was implanted chronically,and measurements of ERNA and movement state were made several monthsafter implantation. By measuring ERNA and movement state at this time,it could be presumed that the electrode array and its neural environmentwere stable. Accordingly, the confirmed relationship between ERNA andmovement state is more representative of the long-term condition of apatient than those relationships measured during acute intraoperativeprocedures, or studies conducted within a few days of electrodeinsertion. It has been found that findings from such short-term studiesmay be confounded by a ‘stun effect’ that is characterized by temporaryalleviation of motor deficits in Parkinson's disease presumably relatedto the surgical implantation procedure rather than application oftherapeutic DBS itself.

ERNA measurements were collected in a similar manner to that describedabove with reference to FIGS. 5a to 6f . Measurements of the patient'smovement functions were also collected. These included estimates ofmuscle rigidity, speed of finger tapping, and facility of opening andclosing the hand.

DBS at different stimulation amplitudes was applied to the implantedelectrode array in a similar manner to that described above. Stimulationamplitudes included zero, 0.667 mA, 1 mA, 1.5 mA, 2.25 mA and 3.375 mA.Non-therapeutic burst stimuli were also provided before and after theperiods of conventional DBS.

FIG. 20 graphically illustrates the results of the movement functiontests. The observations of rigidity, finger tapping and opening/closingof the patient's hand are shown separately, with the average of thosemeasures shown in bold. The observations of patient impairment werescored from 0 (zero) to 4 where 4 indicated the most impairment and zeroindicated the least (or no) movement. This scale is provided on thevertical axis of FIG. 20.

It is evident from FIG. 20 that DBS improved all movement scores, withthe average score showing a marked benefit, particularly at the highestlevels of DBS (2.25 mA and 3.375 mA). Patient movement began to returnto pre-DBS conditions during the final burst washout period, duringwhich stimulation parameters were selected so as to produce notherapeutic effect.

FIGS. 21a, 21b, 21c, 21d and 21e show data extracted from ERNA waveformsrecorded during patterned therapeutic stimulation with amplitudes of0.667 mA, 1 mA, 1.5 mA, 2.25 mA and 3.375 mA respectively. Inparticular, this data is representative of ERNA waveforms recorded inresponse to the final stimulation pulse preceding a period of nostimulation (skipped pulse) as described above (with reference to FIGS.1 and 2). Patterned stimulation was applied over several minutes(represented on the horizontal axis). ERNA waveform peaks arerepresented by darker points. ERNA waveform troughs are represented bylighter points. FIGS. 21f and 21g show ERNA before and after continuousDBS, during periods of burst (non-therapeutic) stimulation.

Taken together, the results shown in FIGS. 20 and 21 show that there isa clear correlation between ERNA and the effectiveness of DBS onalleviating movement disorders. Accordingly, these results providefurther evidence that characteristics of ERNA may be used to control DBSparameter settings to optimize therapy for individual patients.

For example, if the measured ERNA waveform shows a peak at around 7 msand an adjacent peak just below 11 ms (as shown in FIGS. 21d and 21e )then it can be assumed that DBS is effective at reducing symptoms. Peaksat these times occurred only when stimulation was applied at 2.25 mA and3.375 mA, corresponding to DBS conditions where the patient's movementfunctions were less impaired (see FIG. 20). In this case, the DBSwaveform can be adjusted to reduce the energy being applied to thebrain. Such adjustment may comprise adjusting one or more of frequency,amplitude, pulse-width, net charge, or morphology of the stimulus. Suchadjustment can minimize battery usage, reduce adverse side-effectsassociated with DBS, and improve safety of chronic stimulation.Otherwise, if the measured ERNA waveform shows the correspondingadjacent peaks below 7 ms and 11 ms respectively, then it can be assumedthat DBS is not effective and the amplitude of DBS should be increased.For example, FIG. 21c shows adjacent peaks at approximately 6 ms and 9ms in response to a stimulation amplitude of 1.5 mA, which was lesseffective at alleviating motor dysfunction as evidenced by FIG. 20.

In another example, if there are two adjacent peaks present in the ERNAwaveform and they are separated in time by more than approximately 3.5ms, as is the case in FIGS. 21d and 21e , then it can be assumed the DBSis effective. If, on the other hand, the time difference betweencorresponding adjacent peaks is less than 3.5 ms, as is the case inFIGS. 21a and 21b , then it can be assumed that DBS is ineffective. TheDBS waveform can then be controlled to maintain DBS parameters (e.g.frequency, amplitude, pulse-width, net charge, or morphology) at levelswhich provide effective symptom relief whilst preferably also minimizingbattery usage, reduce adverse side-effects associated with DBS, andimprove safety of chronic stimulation.

Whilst the results shown in FIGS. 20 and 21 show a relationship betweenmeasured ERNA and DBS amplitude in particular, it will be appreciatedthat a relationship exists between measured ERNA and any other parameterof the DBS waveform, including but not limited to frequency, amplitude,pulse-width, overall net charge, and morphology.

It will also be appreciated that delays in an initial peak in an ERNAwaveform and delays between ERNA peaks are likely to bepatient-specific. Advantageously, any reliance on such data forcontrolling DBS stimulation will be based on an initial characterizationof ERNA waveforms and movement impairment associated with each patientin order to generate a regime for stimulation control (e.g. closed loopcontrol).

As has been mentioned briefly above with reference to FIGS. 20 and 21,the identification of a correlation between changes in resonantbehaviour of stimulated neural circuits and a patient's disease symptomspresent several opportunities to improve aspects of DBS therapy,including but not limited to techniques for initial implantation andsubsequent repositioning of DBS electrodes, together with techniques forsetting parameters of DBS stimulation and using feedback to adjust DBSparameters in real time whilst DBS therapy is underway.

ERNA Measurements in Subjects Under General Anaesthetic

In addition to confirmation of the effects of DBS in patients withchronically implanted electrodes, the inventors have determined thatERNA responsive to DBS is present and measurable in patients undergeneral anaesthetic. FIGS. 27 to 33 provide comparisons of ERNA recordedwith patients awake and under general anaesthetic. For each of theseFigures, implanted electrodes were stimulated with monopolar symmetricbiphasic pulses with amplitudes of 3.38 mA, a frequency of 130 Hz and a60 μs phase, temporally patterned into bursts of ten consecutive pulsesevery second. The electrodes were implanted as described above. ERNA wasmeasured in left and right STNs of 21 human patients awake and undergeneral anaesthetic using various induction and maintenance agents, asset out in Table 1 below.

TABLE 1 Patient Maintenance ID agents Dosage I040 Propofol/ Propofol 3.0μg/ml, Remifentanil remifentanil 0.6 μg/kg/min I041 Sevoflurane/Propofol 80 mg bolus, remifentanil Remifentanil 0.08 μg/kg/min,sevoflurane end-tidal 1.4% (~0.8 MAC) I042 Sevoflurane/ Propofol 60 mgbolus, sevoflurane end-tidal Remifentanil 1-1.2% (0.5 MAC), remifentanil(0.15- 0.2 μg/kg/min) I043 Sevoflurane/ Sevoflurane 1-1.2% (0.5 MAC),remifentanil Remifentanil 0.1 μg/kg/min I045 Propofol/ Propofol 2.4μg/ml, remifentanil 0.08 μg/kg/min Remifentanil I046 Propofol/ Propofol2.4 μg/ml, remifentanil 0.08 μg/kg/min Remifentanil I047 SevofluranePropofol 60 mg bolus, fentanyl 100 μg bolus, sevoflurane end-tidal 1.5%(0.75 MAC (not age-specific) I048 Sevoflurane Propofol 180 mg bolus, 100μg fentanyl bolus, sevoflurane end-tidal 1.6% (MAC~1) I051 SevofluranePropofol 100 mg bolus, 100 μg fentanyl bolus, sevoflurane end-tidal 2.0%(MAC 1.2) I052 Sevoflurane Propofol 160 mg bolus, 100 μg fentanyl bolus,sevoflurane end-tidal 1.8-1.9% (MAC 1.1) I053 Propofol/ Propofol 0.3ml/hr (3 μg/ml), remifentanil Remifentanil 0.14 μg/kg/min, fentanyl 150μg I054 Not recorded Not recorded I055 Sevoflurane Fentanyl 150 μgbolus, propofol 120 mg bolus, sevoflurane end-tidal 1.4-1.9% (0.7-0.9MAC- 0.7 during test) I056 Sevoflurane/ Propofol 120 mg bolus,sevoflurane 1.5% end- Remifentanil tidal (0.7 MAC), remifentanil 0.2μg/kg/min I057 Sevoflurane/ Propofol 150 mg bolus, sevoflurane 1.4% end-Remifentanil tidal (0.75 MAC), remifentanil 0.2 μg/kg/min I059 Propofol/Fentanyl 100 μg bolus, propofol 1.6-4.3 mg/ml, Alfentanil alfentanil 0.3μg/kg/min I060 Propofol/ Fentanyl 100 μg bolus, propofol 1-5 mg/mlAlfentanil? (3.6 mg/ml at time of experiment), alfentanil 1 mg over ~20min I061 Propofol/ Fentanyl 100 μg bolus, propofol 2.8 mg/ml Fentanyl?/(0.14 μg/kg/min), fentanyl 12.5 μg/hr, Alfentanil? Alfentanil 600 μgI063 Sevoflurane/ Propofol 120 ml bolus?, 1.2% end-tidal (0.7Remifentanil MAC) sevoflurane, remifentanil 0.2 μg/kg/min I065 Propofol/Fentanyl 150 μg bolus?, propofol 3.0 μg/ml, Remifentanil remifentanil0.14 μg/kg/min I066 Propofol/ Fentanyl 125 μg bolus, fentanyl 25 μgbolus, Remifentanil propofol 2.9 μg/ml, remifentanil 0.12 μg/kg/min

FIGS. 27 and 28 provide a comparison of ERNA measured in a patient atelectrode implantation (black) and in the same patient under generalanaesthesia 560 days after implantation. This patient is not included inthe above table. The data shown in these figures was collected from apatient with Parkinson's disease implanted with an electrode array. Theelectrode array was implanted chronically, and measurements of ERNA andmovement state were made both at implantation and 560 days afterimplantation. On the 560^(th) day after implantation, generalanaesthesia was induced a 130 mg bolus of propofol and remifentanyl 0.2μg/kg/min and maintained using remifentanil 0.2 μg/kg/min and isoflurane0.6% end tidal. FIG. 27 is a graph showing ERNA measured duringimplantation (black) and under general anaesthetic (grey). FIG. 28 is agraph showing the variation of ERNA across four electrodes (numbered 1,2, 3 and 4) of an array (such as the Medtronic 3387 electrode array) atimplantation (black) and 560 days later under general anaesthetic. Theseresults show that despite chronic electrode implantation and thepresence of general anaesthetic, ERNA was observed in the patient withcomparable amplitude and positional variation to those recorded atimplantation while the patient was awake (not under generalanaesthetic). Additionally, it can be seen that general anaesthesia hassome effect on the morphology and amplitude of ERNA in patients, mostnotably resulting in a slight reduction in amplitude of ERNA, but thegeneral trend across electrodes in response to stimulation conditionsremains substantially similar

FIGS. 29 and 30 provide a comparison of ERNA measured in a patient bothawake at electrode implantation (black) and under general anaestheticshortly after electrode implantation (grey) in both the left (FIG. 29)and right (FIG. 30) subthalamic nucleus (STN). ERNA was first measuredimmediately after electrode implantation. General anaesthesia was theninduced with an 80 mg bolus of propofol and maintained with sevoflurane0.8 minimum alveolar concentration (MAC) and remifentanil0.08/μg/kg/min. Under general anaesthetic, further measurements of ERNAwere made via the implanted electrodes.

Referring to each of FIGS. 29 and 30, in each column of four plots ineach Figure, the ERNA measured at four electrodes (numbered 1, 2, 3 and4) of a Medtronic 3387 electrode array are shown, each column showingsuch ERNA in response to DBS stimulation at a different one of the fourelectrodes. The electrode being stimulated is denoted at the top of eachcolumn (Electrode stim 1, Electrode stim 2, Electrode stim 3, andElectrode stim 4). These plots show that ERNA detected at electrodesresponsive to DBS stimulation (particularly at electrodes 2, 3 and 4)remain present whilst the patient is under general anaesthetic and haveof similar amplitude to the ERNA detected while the patient is awake.

FIGS. 31 and 32 provide a further comparison of awake and generalanaesthetic ERNA presence in patient ID number I042 shown in Table 1.ERNA was measured with a patient both awake at electrode implantation(black) and under general anaesthetic shortly after electrodeimplantation (grey) in both the left (FIG. 31) and right (FIG. 32)subthalamic nucleus (STN). For the patient the subject of FIGS. 31 and32, general anaesthetic was induced with 60 mg bolus of propofol andmaintained with sevoflurane 0.5 MAC and remifentanil 0.15-0.2 μg/kg/min.

In each column of four plots in each of FIGS. 31 and 32, the ERNAmeasured at four electrodes (numbered 1, 2, 3 and 4) of a Medtronic 3387electrode array are shown, each column showing such ERNA in response toDBS stimulation at a different one of the four electrodes. The electrodebeing stimulated is denoted at the top of each column (Electrode stim 1,Electrode stim 2, Electrode stim 3, and Electrode stim 4). As with thepatient pertaining to FIGS. 29 and 30, FIGS. 31 to 32 evidence that ERNAdetected at electrodes responsive to DBS stimulation (particularly atelectrodes 2, 3 and 4) remain present whilst the patient is undergeneral anaesthetic and have of similar amplitude to the ERNA detectedwhile the patient is awake. Additionally, these results evidence thatvariations in anaesthetic dosage regimes do not seem to substantiallyaffect the measured ERNA.

FIG. 33 provides a further comparison of awake and general anaestheticERNA presence in patient ID number I040 shown in Table 1. ERNA wasmeasured with a patient both awake at electrode implantation (black) andunder general anaesthetic shortly after electrode implantation (grey) inthe left subthalamic nucleus (STN). For the patient the subject of FIG.33, general anaesthetic was induced and maintained with a targetcontrolled infusion of propofol 3.0 μg/ml and remifentanil 0.6μg/kg/min.

In each column of four plots in FIG. 33, the ERNA measured at fourelectrodes (numbered 1, 2, 3 and 4) of a Medtronic 3387 electrode arrayare shown, each column showing such ERNA in response to DBS stimulationat a different one of the four electrodes. The electrode beingstimulated is denoted at the top of each column (Electrode stim 1,Electrode stim 2, Electrode stim 3, and Electrode stim 4). These datafurther evidences that ERNA detected at electrodes responsive to DBSstimulation (particularly at electrodes 2, 3 and 4) remain presentwhilst the patient is under general anaesthetic. Additionally, theseresults evidence that ERNA is measurable in the presence of variousdrugs and anaesthetic agents.

The above results show that ERNA can be used for the guidance ofelectrodes during implantation surgery to the most beneficial sites forstimulation in anesthetized patients as well as those patients whoremain awake during surgery. Furthermore, the results show that avariety of drugs and drug regimens conventionally used in anaesthesiacan be used during such implantation surgery without detrimentallyaffecting the presence and use of ERNA for the guidance of electrodes.

FIG. 34 is a box and whisker plot showing median, range andinterquartile range of ERNA amplitude measured at four electrodes(numbered E1, E2, E3 and E4) of an implanted Medtronic 3387 electrodearray in the 21 patients shown in Table 1 both awake and under generalanaesthetic (asleep). This plot shows that for electrodes targeted atthe STN of the subjects (E2 and E3)—which have large ERNA—there is asignificant reduction in ERNA amplitude when under general anaesthetic.Electrodes E1 and E4 are typically outside the STN and have small or noERNA.

FIGS. 35a to 35c shows rank plots of ERNA for the 21 patients awakeversus under general anaesthetic. For each STN of the 21 patients,electrodes were ranked from 1 to 4 according to measured ERNA amplitude,rank 1 being the highest amplitude ERNA and rank 4 being the lowestamplitude. The shading of each square represents a percentage matchwhere electrodes measured ERNA amplitudes in the same rank in both awakeand anaesthetised states. A 100% match is represented by a black square.A 0% match is represented by a white square. FIG. 35a includes data forall 21 patients (2 STNs in each patient). FIG. 35b includes data forthose patients in which anaesthesia was induced by propofol (9 patients,18 STNs). FIG. 35c includes data for those patients in which anaesthesiawas induced by sevoflurane (11 patients, 22 STNs).

Across all STNs tested, electrodes measuring the largest ERNA (rank 1)in the awake state also measure the largest ERNA amplitude (rank 1) inthe asleep state for 32 of the 42 STNs. Electrodes measuring the largestERNA amplitude (rank 1) in the awake state also measure the secondlargest ranked ERNA amplitude (rank 2) in the asleep state for theremaining 10 of the 42 STNs. This indicates that for the majority ofSTNs tested, electrodes measuring the largest ERNA amplitude in theawake state also measure the largest ERNA amplitude under generalanaesthetic. This further indicates that for all STNs tested, electrodesmeasuring the largest ERNA amplitude in the awake state either measurethe largest ranked ERNA amplitude or second largest ranked ERNAamplitude under general anaesthetic. It can also be seen, from acomparison of FIGS. 35a to 35c ,that the above pattern is substantiallycorrelated across all anaesthetic agents.

FIG. 36 provides a further comparison of awake (black) and generalanaesthetic (grey) ERNA for patient ID041 in Table 1. It can be seenthat general anaesthetic causes an inflection in the first peak of theresonant response. It is suspected that this inflection may be a resultof the superposition of two responses that combine with each other inthe measured ERNA. It is proposed that general anaesthesia may affectthese responses differently causing the inflection shown in FIG. 36. Aconsequence of the inflection shown in FIG. 36 is that for patientsunder general anaesthetic, the duration between the first ERNA peak andthe second ERNA peak in the measured response may differ substantiallyfrom the duration between the second ERNA peak and third ERNA peak (andalso the duration between subsequent peaks—third and fourth, fifth andsixth etc.). When using ERNA for diagnosis and control, particularly inpatients under general anaesthetic, it may therefore be preferable tomeasure/monitor peak to peak duration/latency as opposed to measuringthe frequency of the resonant response over multiple peaks. For example,it may be preferably to measure the duration between first and secondpeaks in an ERNA, in addition to the duration between second and thirdpeaks in that ERNA.

FIGS. 37a is a plot showing median, range and interquartile range ofERNA peak-to-peak latency between first and second peaks for largestranked amplitude (rank 1) ERNA for 36 STNs in brains of patients shownin Table 1 both awake and under general anaesthetic (asleep). FIG. 37bis a plot showing median, range and interquartile range of ERNA peak topeak latency between second and third peaks for largest ranked amplitude(rank 1) ERNA for the 36 STNS of patients shown in Table 1 both awakeand under general anaesthetic (asleep). It is noted that peak-to-peaklatency was not measurable for the remaining 6 STNs of the 42 STNstested (21 patients), resulting in a sample size of n=36 STNs in FIGS.37a and 37 b.

In both of FIGS. 37a and 37b , the ERNA peak-to-peak latency isrepresented separately for all patients, patients induced by propofol,and patients induced by sevoflurane. It can be seen that for allpatients, peak-to-peak latency increases (both between first and secondpeaks and between second and third peaks) in patients under generalanaesthetic. This suggests that general anaesthetic increasespeak-to-peak latency, i.e. slows the average frequency of response. Itcan also be seen from the above described figures that the peak 1 topeak 2 latency is shorter than peak 2 to peak 3 latency for awakepatients, whereas for patients under general anaesthetic the opposite istrue; peak 1 to peak 2 latency is longer than peak 2 to peak 3 latency.

From the above it can be ascertained that ERNA is present in humansubjects under general anaesthetic. It can also be ascertained that peakto peak duration or latency of ERNA can be used to identify optimumlocations for therapeutic stimulation.

The inventors have also determined that ERNA is present in sheep, asillustrated by FIGS. 28 to 43. Adult female sheep were anaesthetisedwith a constant flow of isoflurane (˜2%) in air, and the vital signs(heart rate, end-tidal CO2, pulse oximetry, palpebral reflex) monitoredfor the duration of the surgery. Neural activity was invoked bystimulating a single ring electrode of an electrode array and wasrecorded from 11 other channels with a combination ring electrodes andwire electrodes. The electrode array was implanted in the region of theSTN of the sheep. The recorded ERNA shown in FIGS. 38 to 43 was measuredfrom ring electrodes adjacent to the stimulating electrode with adistance of 1.5 mm centre to centre.

The implanted electrodes were stimulated with monopolar symmetricbiphasic pulses with amplitudes of 3.375 mA (FIGS. 38 and 41), 5.063 mA(FIGS. 39 and 42) and 7.594 mA (FIGS. 40 and 43), at a frequency of 130Hz and with a 60 μs phase. The stimulus was temporally patterned intobursts of ten consecutive pulses every second. A total of 10 bursts often consecutive pulses were administered at each amplitude.

FIGS. 38 to 40 show a resultant ERNA for a first sheep subject,responsive to the above described stimulus at amplitudes of 3.375 mA,5.063 mA and 7.594 mA respectively. FIGS. 41 to 43 show resultant ERNAfor a second sheep subject, again responsive to the above describedstimulus at amplitudes of 3.375 mA, 5.063 mA and 7.594 mA respectively.These figures illustrate that despite the sheep being under generalanaesthetic, resonant neural activity is evoked from deep brainstimulation. Additionally, these results show that the use of inhaledisoflurane as an anaesthetic does not affect the presence of ERNA atleast in sheep subjects.

A number of practical applications of the above described evokedresonant neural activity will now be discussed with reference to severalembodiments. In the embodiments, one or more electrode leads may be usedfor stimulation of one or more neural structures within one or bothhemispheres of the brain, each lead comprising one or more electrodeslocated near the tip of each lead. Each of the electrodes may be usedfor stimulation, monitoring, or both stimulation and monitoring. One ormore of these electrodes may be implanted. Implanted electrodes may beused independently or in addition to one or more electrodes placed onthe outside of the brain or skull.

A typical DBS electrode lead tip 70, such as that incorporated into theMedtronic (RTM) DBS Lead Model 3387, is shown in FIG. 8. The lead tip 70comprises a first electrode 72 a, a second electrode 72 b, a thirdelectrode 72 c, and a fourth electrode 72 d. Once implanted into thebrain, each of the electrodes 72 a, 72 b, 72 c, 72 d may be used toapply a stimulus to one or more neural structures or monitor andoptionally record the evoked response (including ERNA) from neuralcircuits to the stimulus. In other embodiments, leads with moreelectrodes or electrodes with different sizes or topologies may be used.In addition, one or more reference electrodes may be located at a remotesite and used to complete the electrical circuit when one or moreelectrodes on the DBS lead are activated for stimulation or used forsignal monitoring.

The target location for the lead tip 70 varies dependent on the neuralstructure. Example target structures include but are not limited to thesubthalamic nucleus (STN), the substantia nigra pars reticulata (SNr),and the globus pallidus interna (GPi).

FIG. 9 shows the lead tip 70 implanted into a brain at a targetstructure, in this case the subthalamic nucleus (STN) 82. It will beappreciated that intersecting the electrode tip 70 with the subthalamicnucleus (STN) 82, which has a typical diameter of 5 to 6 mm, can be avery difficult surgical task. Techniques such as stereotactic imaging,microelectrode recordings, intraoperative x-ray imaging, and applyingtherapeutic stimulation whilst monitoring patient symptoms, arecurrently used to localize the electrode tip 70. However, these methodscan lack accuracy. Additionally, existing methods usually require thepatient to be awake for the procedure, since voluntary responses fromthe patient can be used to confirm that the electrode is at a suitablelocation relative to a target structure in the brain. For this reason,many potential recipients of DBS therapy turn down the option becausethey are not comfortable with having to be awake during the surgicalprocedure.

The accuracy of locating electrodes of the electrode tip 70 within atarget structure can be greatly increased by using a series of patternedstimulations to generate and measure an evoked resonant response from aneural target. Such techniques can obviate the need for the patient tobe awake during the implantation procedure, since an electrode can belocated much more accurately at the correct location within the brainand relative to a target neural structure. This means that patients canbe under sedation or general anaesthetic during the surgery since nopatient feedback is required to locate the electrode to a satisfactorydegree of accuracy.

An example DBS delivery system 90 according to an embodiment of thepresent disclosure is illustrated in FIG. 10. The system 90 comprisesthe lead tip 70 of FIG. 8 including the plurality of integratedelectrodes 72 a, 72 b, 72 c, 72 d, together with a processing unit 92, asignal generator 94, a measurement circuit 96 and an optionalmultiplexer 98. The processing unit comprises a central processing unit(CPU) 100, memory 102, and an input/output (I/O) bus 104 communicativelycoupled with one or more of the CPU 100 and memory 102.

In some embodiments, the multiplexer 98 is provided to control whetherthe electrodes 72 a, 72 b, 72 c, 72 d are connected to the signalgenerator 94 and/or to the measurement circuit 96. In other embodimentsthe multiplexer may not be required. For example, the electrodes 72 a,72 b, 72 c, 72 d may instead be connected directly to both the signalgenerator 94 and the measurement circuit 96. Although in FIG. 10 all ofthe electrodes 72 a, 72 b, 72 c, 72 d are connected to the multiplexer98, in other embodiments, only one or some of the electrodes 72 a, 72 b,72 c, 72 d may be connected.

The measurement circuit 96 may include one or more amplifiers anddigital signal processing circuitry including but not limited tosampling circuits for measuring neural responses to stimulation,including ERNA. In some embodiments the measurement circuit 96 may alsobe configured to extract other information from received signals,including local field potentials. The measurement circuit 96 may also beused in conjunction with the signal generator 94 to measure electrodeimpedances. The measurement circuit 96 may be external to or integratedwithin the processing unit 92. Communication between the measurementcircuit 96 and/or the signal generator 94 on the one hand and the I/Oport on the other may be wired or may be via a wireless link, such asover inductive coupling, Wi-Fi®, Bluetooth® or the like. Power may besupplied to the system 90 via at least one power source 106. The powersource 106 may comprise a battery such that elements of the system 90can maintain power when implanted into a patient.

The signal generator 94 is coupled via the multiplexer 98 to one or moreof the electrodes 72 a, 72 b, 72 c, 72 d and is operable to deliverelectrical stimuli to respective electrodes based on signals receivedfrom the processing unit 92. To this end, the signal generator 94, themultiplexer 98 and the processing unit 92 are also communicativelycoupled such that information can be transferred therebetween. Whilstthe signal generator 94, multiplexer 98, and the processing unit 92 inFIG. 10 are shown as separate units, in other embodiments the signalgenerator 94 and multiplexer may be integrated into the processing unit92. Furthermore, either unit may be implanted or located outside thepatient's body.

The system 90 may further comprise one or more input devices 108 and oneor more output devices 110. Input devices 108 may include but are notlimited to one or more of a keyboard, mouse, touchpad and touchscreen.Examples of output devices include displays, touchscreens, lightindicators (LEDs), sound generators and haptic generators. Input and/oroutput devices 108, 110 may be configured to provide feedback (e.g.visual, auditory or haptic feedback) to a user related, for example, tocharacteristics of ERNA or subsequently derived indicators (such asproximity of the electrode 70 relative to neural structures in thebrain. To this end, one or more of the input devices 108 may also be anoutput device 110, e.g. a touchscreen or haptic joystick. Input andoutput devices 108, 110 may also be wired or wirelessly connected to theprocessing unit 92. Input and output devices 108, 110 may be configuredto provide the patient with control of the device (i.e. a patientcontroller) or to allow clinicians to program stimulation settings, andreceive feedback of the effects of stimulation parameters on ERNAcharacteristics.

One or more elements of the system 90 may be portable. One or moreelements may be implantable into the patient. In some embodiments, forexample, the signal generator 94 and lead 70 may be implantable into thepatient and the processing unit 92 may be external to the patient's skinand may be configured for wireless communication with the signalgenerator via RF transmission (e.g. induction, Bluetooth®, etc.). Inother embodiments, the processing unit 92, signal generator 94 and lead70 may all be implanted within the patient's body. In any case, thesignal generator 94 and/or the processing unit 92 may be configured towirelessly communicate with a controller (not shown) located external tothe patient's body.

One embodiment of the present disclosure provides a system and methodfor localizing the lead tip 70 within a target structure of the brainusing measured ERNA. During an operation for implantation of the leadtip 70 into the brain, instead of relying on low accuracy positioningtechniques as described above to estimate the location of electrodesrelative to neural structures within the brain, the system 90 may beused to provide real-time feedback to the surgeon based oncharacteristics such as the strength and quality of evoked responsesignals received from one or more electrodes of the lead tip 70. Thisfeedback may be used to estimate position within the target structure inthree dimensions and to inform the decision of whether to reposition theelectrodes or remove and reimplant the electrodes along a differenttrajectory.

FIG. 11 shows a general example of such a process. The process begins atstep 112 with an electrode lead tip such as that described withreference to FIG. 8 being advanced during surgery towards a targetneural structure along a predefined trajectory. The step size (orspatial resolution) by which the electrode lead is advanced may bechosen by the surgeons and/or clinicians. In some embodiments, the stepsize is 1 mm At step 114, evoked responses, including ERNA, are measuredby applying a patterned stimulus such as those described above to anelectrode of the lead tip 70. The stimulus may be applied for the wholetime whilst the lead tip 70 is being implanted. Alternatively, thepatterned signal may be repeated a predetermined number of times, suchas 10 times. The evoked response may be measured at the same electrodeas that used to apply the stimulus or may be measured at one or moredifferent electrodes. By doing so, a more accurate estimate of thelocation of each electrode relative to the target neural structure maybe provided. Steps 112 and 114 are repeated until the electrode lead tiphas been inserted to the maximum allowable depth, which may be in thetarget neural structure or slightly beyond it.

By repeating steps 112 and 114, a profile or map of evoked responses atdifferent locations along the insertion trajectory may be generated. Theprofile of evoked responses may include measurements from multipleelectrodes or from just one electrode. The profile of evoked responsesat different depths may be output to the one or more output devices 110.The profile of evoked responses is then compared at step 118 in order todetermine whether a preferred electrode location can be identified. Theidentification of preferred electrode location may be based on differentERNA features, including relative differences between or spatialderivatives of amplitude, rate of decay, rate of change, and frequency,at different insertion positions (e.g. the location that produces thelargest resonances).

The identification of a preferred electrode location may also be basedon comparison with template ERNA activity, where the templates have beenderived from recordings from other patients. The profile of evokedresponses may also be used to estimate the trajectory of the electrodelead 70 through the target neural structure, including the boundaries ofthe structure and the region intersected (e.g. the trajectory passedthrough the medial or lateral region). The profile of evoked responsesmay also be used to estimate the proximity to the target structure, inthe event that the target structure is not intersected by the insertiontrajectory.

If at step 120 a preferred electrode location can be identified, theelectrode lead tip 70 can be repositioned at step 122, such that anelectrode is positioned at the preferred location. Alternatively, forembodiments that include electrode lead tips with a large number ofelectrodes, the electrode positioned closest to the preferred locationcan be nominated for subsequent use in applying therapeutic stimulation.If at step 120 a preferred location cannot be identified, the surgeonand/or clinician may choose to remove the electrode and re-implant alonga different trajectory.

Another embodiment of the present disclosure provides a system andmethod for determining the relative positions of an array of electrodeswith respect to a target neural structure and then selecting a preferredelectrode to use for applying therapeutic stimulation. This processcould be performed during electrode implantation surgery to assist inthe positioning of electrodes, or with previously implanted electrodeswhen programming the device to deliver therapeutic stimulation. Astimulus may be applied at more than one of the electrodes of the array,for example two or more of electrodes 72 a, 72 b, 72 c, 72 d in the caseof electrode array 70. Where a patterned stimulation regime is used,sequential bursts of a stimulus pattern may be applied to different onesof the electrodes 72 a, 72 b, 72 c, 72 d. Alternatively, a full stimuluspattern may be applied at one electrode, followed by another fullstimulus pattern at another electrode. By doing so, a determination maybe made concerning which electrode of an electrode array is positionedbest to provide therapeutic stimulation to one or more of the targetneural structures; for example, which of the electrodes 72 a, 72 b, 72c, 72 d is best positioned within a target neural structure.

FIG. 12 illustrates an example process 130 for measuring evoked responsefrom an array of multiple electrodes. At step 132, a stimulus is appliedto the first electrode of an array of X electrodes (electrode 72 a inthe case of the lead tip 70). The stimulus applied may be a burstpatterned stimulus as described above. The evoked response from a targetneural structure is measured at one or more of the electrodes in thearray at step 134. In the case of the lead tip 70, for example, theevoked response may be measured at the second, third and fourthelectrodes 72 b, 72 c, 72 d when the first electrode 72 a is beingstimulated. In some embodiments, the evoked responses received at thestimulating electrode may also be recorded and optionally stored inmemory. Once the evoked response has been measured at each electrode,another electrode is selected for stimulation. This may be achieved byincrementing a counter, as shown in step 138, after the process haschecked at step 136 to see whether all electrodes in the array of Xelectrodes have been stimulated, i.e. whether the process has cycledthrough all of the electrodes in the system. If there are electrodesremaining to be stimulated, then the process repeats, applying astimulus to the next selected electrode in the array. If all electrodesin the array have been stimulated and an evoked response to stimulationat each electrode measured and recorded, the resultant measured evokedresponses are then processed at step 140.

Processing the evoked responses may involve comparing different ERNAfeatures, including relative differences between or spatial derivativesof amplitude, rate of decay, rate of change, and frequency, acrossdifferent combinations of electrodes used for stimulation andmeasurement. For example, the processing may involve identifying theelectrode that measures the largest evoked resonance amplitude for eachstimulation condition. The identification of the preferred electrodelocation may also be based on a comparison with template ERNA activity.Templates may be derived from recordings from other patients or from oneor more models or simulations. The processing may equally involvedetermining a peak-to-peak latency between peaks in the response, suchas the duration between first and second peaks in the response, theduration between second and third peaks in the response, or acombination of both. The relative peak-to-peak latency may be used toidentify the best electrode for stimulation.

Based on the processing of the evoked responses, a preferred electrodeto use for therapeutic stimulation may be chosen at step 142. Theresults of the ERNA processing and a recommendation for the preferredelectrode may be output to the one or more output devices 110. If theprocess has been performed during surgery, the results of the ERNAprocessing may also be used to determine which electrodes are within thetarget neural structure and whether to reposition the electrode array.The results may also be used to generate one or more templates forfuture processing of evoked responses in the same or different patients.

FIG. 13 shows an example of the evoked responses measured at each of thefirst, second and fourth electrodes 72 a, 72 b, 72 d based on patternedstimulation applied to the third electrode 72 c. This examplecorresponds to one iteration of steps 132 and 134 of process 130 shownin FIG. 12. The stimulated electrode 72 c is represented with thecrossed axes. Firstly, it is shown that a resonant response over severalcycles can be measured using the novel patterned stimulus. Secondly, itcan be seen that the response at the second electrode 72 b has thelargest amplitude, the amplitude of response at the fourth electrode 72d has the smallest amplitude, and the amplitude of the evoked responseat the first electrode 72 a is substantially less than that at thesecond electrode 72 b but slightly greater than that at the fourthelectrode 72 d. These results indicate that the second electrode 72 b isclosest to or within the target neural structure and the first andfourth electrodes 72 a, 72 d are outside of the target neural structure.

Whilst in the above example the evoked response is measured at threeelectrodes, in other embodiments, the evoked response may be measured atone or two or any number of electrodes in any configuration. Forexample, ERNA could be measured and/or recorded from differentcombinations of electrodes. Additionally or alternatively, measurementelectrodes may be implanted in and/or positioned external to the brainor skull.

FIG. 14 graphically illustrates example evoked responses to stimulationin accordance with the process 130 of FIG. 12 applied to the lead tip 70of the system 90 shown in FIG. 10. Each column of graphs represents oneof four stimulation conditions with the stimulated electrode representedby the crossed panel, i.e. each column is an iteration of steps 132 and134 of process 130. The data shown in FIG. 14 was measured with thesecond and third electrodes 72 c, 72 d positioned within the subthalamicnucleus (STN) of a patient's brain. It can be seen that the largestevoked responses are observed at each of the second and third electrodes72 b, 72 c when the other of those electrodes 72 c, 72 b is stimulated.Accordingly, by comparing the measured evoked responses at eachelectrode in response to stimulation at another electrode, adetermination can be made firstly of whether any of the electrodes arepositioned within the target neural structure, secondly whether any ofthe electrodes are positioned at an optimum location within the targetneural structure, and thirdly the direction and/or distance of aparticular electrode from that target neural structure. In someembodiments, one or more of the presence, amplitude, natural frequency,damping, rate of change, envelope, and fine structure of an evokedresonant response to a stimulus may be used to identify the mosteffective electrode in an electrode array. Additionally, it can be seenthat the evoked responses vary depending on the position of theelectrode used for stimulation, illustrating the feasibility of usingthe process illustrated in FIG. 11 to localize electrodes within atarget neural structure.

The process 130 of FIG. 12 may be repeated using different stimulationparameters (e.g. using different stimulation amplitudes or frequencies)or with more than one stimulating electrode in step 132 (e.g.stimulation applied concurrently through multiple electrodes on one ormore electrode leads). The response characteristics obtained may be usedto aid current steering (e.g. setting the distribution of currentsacross electrodes that are active simultaneously) and the selection ofactive electrodes (e.g. which electrodes to use for stimulation). Forexample, response characteristics can be used to estimate the spatialspread of activation relative to the target area. Using thisinformation, the stimulation profile may be shaped using two or moreelectrodes to direct stimulation to particular areas of the brain, i.e.towards a target structure, and away from areas which the clinician doesnot wish to stimulate.

In a further embodiment, ERNA can also be used to optimize stimulationparameters used to target various medical conditions. For instance, oncean electrode array such as the lead tip 70 has been accurately locatedwithin a target neural structure, the setting of stimulation parametersfor therapeutic DBS can be aided by measuring ERNA, improving accuracyand time- and cost-efficiency, and reducing undesirable side-effects.

The change in elicited resonant activity for different stimulationparameters may be used to optimize stimulation settings. Such processescan enable therapy to be tailored to the individual needs of patientsand can be performed with minimal clinical intervention. In someembodiments, one or more of the presence, amplitude, natural frequency,peak-to-peak latency between (two peaks or sets of two or more peaks),damping, rate of change, envelope, and fine structure of an evokedresonant response to a stimulus may be used to optimize stimulation.Such response characteristics may be used to adjust amplitude,frequency, pulse width, and shape of a stimulation waveform.

A parameter of therapeutic stimulation that is particularly difficult toset using state of the art techniques is stimulation frequency. This ispartly because optimum stimulation frequency can vary from patient topatient; typically between around 90 Hz to around 185 Hz. In embodimentsof the present disclosure, one or more of the above describedcharacteristics of ERNA may be used to set frequency of stimulation(e.g. the time period t2 between pulses in a burst). For example, thestimulation frequency might be selected to approximate a multiple orsubmultiple of a frequency component of the ERNA, such as the estimatedfundamental frequency of the ERNA.

It will be appreciated that some or all of the parameters listed abovemay have synergistic or adverse effects on one another and thus theeffectiveness of treatment. Accordingly, in some embodiments, knownoptimization techniques such as machine learning or particle swarm maybe implemented to find an optimal set of parameter values within themultidimensional parameter space. Such techniques may involve aniterative process of trying a selection of different parameter settingsto determine the most effective parameter values based on the monitoredERNA.

To further optimize therapeutic DBS, the above techniques for ERNAmonitoring and DBS parameter optimization can be performed on a patientbefore and after administration of medication for relieving symptoms ofa condition. For example, a record of ERNA for a particular patient whois on or off such medication may be used as a benchmark for an evokedresonant response which provides the most benefit to a patient so thatparameters can be tuned to try to replicate such evoked response states.FIG. 15 schematically illustrates a method of determining stimulationparameters based on the ERNA responsive to the stimulation of amedicated patient. At step 144, a stimulus is applied to an implantedelectrode in a target neural structure of a patient before beingadministered with any medication, and the ERNA from the stimulus ismeasured and recorded at step 146. The patient is then medicated at step148. For example, a clinician may administer a dose of a drug (e.g.,levodopa) to the patient. At steps 150 and 152 the process ofstimulation and measurement of resonant response are repeated. The ERNAbefore and after the medicament is administered is then used todetermine stimulation parameters which approximate those of thepatient's medicated state. In particular, DBS parameter settings may bechosen which, when administered, replicate or approximate the transitionfrom the uncontrolled-symptom ERNA to the controlled-symptom ERNA.

In some embodiments, optimization processes may be performed by aclinician when the system 90 is being installed or during a visit to ahealthcare centre. Additionally or alternatively, the optimization maybe run by the patient or may be instigated by the system 90automatically. For example, the system 90 may implement an optimizationprocess periodically (e.g. every day, week or month). In otherembodiments, an optimization process could be initiated on replacementor recharge of a battery, in circumstances where the power source 106includes a battery. Other conditions that could trigger an optimizationprocess include a change in the patient's state, such as whether thepatient is engaged in a fine motor task, a gross motor task, speaking,sleeping, or is sedentary.

In some embodiments, the system 90 may store a series of previouslyoptimized settings in the memory 102. These stored settings maycorrespond to the optimized settings for different patient states (e.g.fine or gross motor activation, sleeping or sedentary) and may includestimulation being applied to different target neural structures. Thepatient may be given the ability to choose which of the storedstimulation settings they want to use at any given time, through the useof a patient controller. Alternatively, the system 90 may automaticallychoose which of the stored stimulation settings to use based onmeasurements of the patients state from electrophysiological signals(e.g. ERNA or local field potentials) recorded from the electrodes 70 bysystem 90 or from measurements taken with input devices 108 of system 90(e.g. accelerometers).

In addition to enhancing the accuracy of locating a DBS electrode in thebrain, choosing electrode configurations for stimulation and optimizingstimulation parameters, ERNA may be used to generate feedback forcontrolling the stimulation of electrodes. In some embodiments, feedbackmay be implemented using the system 90 shown in FIG. 10.

In one embodiment, the system 90 may use a waveform templatecorresponding to a preferred patient state. The template may begenerated using previous recordings of ERNA in a patient with reducedsymptoms. For example, ERNA templates recorded from a medicated patientor a patient receiving effective stimulation treatment may be used.Alternatively, ERNA templates recorded from a healthy patient, e.g. apatient without a movement disorder, may be used. Templates may beconstructed from the average of many recordings from one patient orseveral patients. In some embodiments, selected features of the ERNAwaveform may be used instead of a complete template. For example,parameters of the ERNA such as the dominant frequency and amplitudecomponents and/or temporal features may be used to enable improvedelectrode placement and control of therapeutic stimulation. In someembodiments, preferred ranges for different ERNA characteristics may bedefined (e.g. stimulation is controlled such that the ERNA frequencyremains within 250-270 Hz).

Referring to FIG. 10 and FIG. 16, the processing unit 92 may sendinstructions/signals to the signal generator 94 to generate a patternedstimulation signal which may or may not have been pre-calibrated inaccordance with an embodiment described above. The signal generator 94may then generate the signal at step 160 and apply it to one of theelectrodes 72 a, 72 b, 72 c, 72 d of the lead tip 70 (step 162). Theprocessing unit 92 may then measure the ERNA and monitor one or moreparameters (or characteristics) of the ERNA (step 164). The processingunit 92 may then process the received ERNA data (step 166). In someembodiments, the processing unit 92 may compare the ERNA (or one moreparameters thereof) with a resonant response associated with effectivetherapy (or one or more parameters thereof). Based on the ERNA data, theprocessing unit 92 may then instruct the signal generator to adjust oneor more parameters of the stimulation signal applied to one of theelectrodes 72 a, 72 b, 72 c, 72 d (step 168).

In some embodiments, bursts of stimulation, such as those describedabove, in combination with the monitoring of ERNA may be used toidentify a therapeutic resonant state (e.g. a state which correlateswith good symptom suppression with minimal side effects and/or minimumelectrical power consumption). From this information, therapeuticstimulation parameters required to produce the preferred therapeuticstate may be identified. In some embodiments, these stimulationparameters may be used to apply continuous therapeutic DBS to the targetneural structure.

Probe bursts for identifying resonant activity can be interleaved withthe therapeutic DBS to re-assess the resonant state. These probe burstsmay be implemented on a periodic basis, for example, every 10 seconds.In one embodiment, every 10 seconds, a probe burst may be applied for 1second (e.g. 10 pulses at 130 Hz) and the ERNA assessed. The therapeuticstimulation parameters may then be adjusted or maintained based on theERNA. For example, if there is a change in ERNA relative to the lastprobe burst, the stimulation parameters may be adjusted such that theERNA becomes comparable with the previously measured ERNA and/or thetemplate ERNA and/or an ERNA characteristic is within a desired range.

There are a number of ways in which the therapeutic stimulation may beadjusted based on the measured ERNA. In some embodiments, if theresonant circuit is in a preferred resonant state, e.g. if the measuredERNA substantially matches a template or if an ERNA characteristic iswithin a desired range, the amplitude of the therapeutic stimulation maybe reduced by the signal generator 94 in response to an instruction fromthe processing unit 92. Conversely, if the neural circuit is not in apreferred resonant state, the amplitude of therapeutic stimulation maybe increased by the signal generator 94.

In some embodiments, if a therapeutic resonance is detected, the DBSstimulation may be switched off altogether or until after the next probeburst is applied to generate a measurable ERNA. Then when the next probeburst is applied, if the resonance is no longer therapeutic, the DBSstimulation may be switched back on.

In some embodiments, a comparison of multiple resonant components in asingle measured evoked response may be used as a measure of stimulationefficacy and may be used as a control variable to control stimulationparameters.

In some embodiments, the length of continuous stimulation blocks(between probe bursts) and the duration of the probe bursts may beadjusted to optimize the ERNA. Longer continuous stimulation periods orblocks between probe bursts will reduce the computation load on theprocessing unit 92 and thus increase power efficiency but may alsoresult in greater variation of ERNA from the preferred ERNA and thus areduction in effectiveness of treatment.

There is an inherent requirement for implanted and portable DBS devicesto provide the best treatment of symptoms while minimizing both sideeffects and power consumption. In one embodiment, a method for operatingthe system 90 using closed-loop feedback is provided in which the dutycycle of stimulation is modulated with an aim to minimize stimulationon-time. FIG. 17 illustrates a process which may be performed by thesystem 90. At step 170 a stimulation signal is generated. Parameters ofthe stimulation signal are chosen so as to optimize the ERNA to apreferred resonant state. The stimulus is then applied to an electrodeof the lead tip 70 for a period T at step 172. The period T may be afixed period. Preferably the stimulus is applied continuously orperiodically until a preferred state of ERNA is reached. The therapeuticstimulation is then stopped and the evoked response is measured at oneor more electrodes, the evoked response being to a probe stimuluscomprising one or more bursts of pulses applied to the stimulationelectrode (at step 174). In some embodiments the probe stimulus may beapplied to more than one electrode. In some embodiments, the stimulationelectrode can be used to measure ERNA instead of or in addition to theone or more other electrodes. The system is then maintained in thisstate of monitoring until the ERNA becomes undesirable. In someembodiments, the determination of whether or not the ERNA is in apreferred or therapeutic state may be performed by comparing themeasured response with a template ERNA response or by comparing ameasured ERNA characteristic with a desired range. As soon as it isconsidered that the state is undesirable at step 176, a stimulationsignal is again generated and applied at steps 170 and 172.

FIG. 18 graphically compares a stimulation regime 178 comprising apatterned therapeutic stimulation signal 182 followed by anon-therapeutic patterned stimulation signal (comprising one or morebursts of pulses) 184 and a corresponding characteristic (e.g. resonantfrequency) 180 of the ERNA varying between a preferred state 186 and aless than preferable state 188.

There are several different ways of implementing the patterned signalsof embodiments described herein. FIGS. 19a and 19b illustrate twoexemplary patterning profiles. In FIG. 19a , the patterned profileincludes a period of no stimulation 192 after a continuous stimulationblock 190, followed by a burst of pulses 194 and another period of nostimulation 196. During the period of no stimulation, the ERNA may bemeasured and therapeutic stimulation signal adjusted (if required).

In an alternative embodiment, the system may monitor the ERNA after afinal pulse of continuous stimulation 198 as shown in FIG. 19b . After aperiod of monitoring 200, the therapeutic stimulation may then beadjusted for a period 202 after which the therapeutic stimulation 198may be applied with the adjusted parameters. This regime may also beconsidered as continuous stimulation with periodic missing pulses. Tothis end, the continuous stimulation may be considered as a burst ofpulses, and the period of no stimulation may be considered as the firsttime period t₁ as described with reference to FIG. 2 above.

In other embodiments, instead of omitting stimulation during themonitoring period 200, stimulation may be maintained but with alteredparameters, as described previously with reference to FIGS. 5a and 5b .For example, conventional therapeutic stimulation at a frequency of,e.g. 130 Hz, may be applied during the therapeutic stimulation period198. Then during the monitoring period 200, a stimulus having adifferent frequency, may be applied. The stimulus applied during themonitoring period may be lower than that applied during the stimulationperiod. For example, the stimulation frequency during this period may bein the region of 90 Hz. The frequency of this stimulus during themonitoring period 200 may be low enough to allow for multiple ERNA peaksto be observed. Equally, the frequency of the stimulus applied duringthe monitoring period 200 may be high enough to be within thetherapeutic frequency range for DBS. As mentioned above, the transitionbetween frequencies may be abrupt or, alternatively the change infrequency may be gradual. Applying ramps to the frequency of the pulsesto avoid an abrupt step change in frequency may be advantageous.

Additionally or alternatively, the amplitude of the stimulus appliedduring the monitoring period 200 may differ to that applied during thetherapeutic period 198. For example, the amplitude of the stimulusapplied during the monitoring period 200 may be less than that appliedduring therapeutic stimulation 198. An amplitude ramp may be applied totransition the stimulus between the therapeutic period 198 and themonitoring period 200 over several pulses, to avoid an abrupt stepchange in amplitude.

In some embodiments, characteristics of the stimulus other thanamplitude and frequency may differ between the stimulation period 198and the monitoring period. Examples of such characteristics include, butare not limited to, frequency, amplitude, pulse-width, net charge,electrode configuration, or morphology of the stimulus.

The presence and amplitude of ERNA can be dependent on stimulationamplitude. Accordingly, so as to maintain consistency in ERNAmeasurements, it may be preferable to always use the same pulseparameter settings and in particular the same amplitude for the pulseused to measure ERNA. The last pulse before the period of no stimulationmay therefore be at a fixed amplitude which is independent of theamplitude of stimulation being applied by other pulses (e.g. therapeuticstimulation), so as to minimize any effect due to resonance dependenceon stimulation amplitude or other pulse parameters.

Whilst in embodiments described above, a single electrode array is usedboth to stimulate and record an evoked neural response, in otherembodiments, electrodes may be distributed on multiple probes or leadsin one or more target structures in either or both brain hemispheres.Equally, electrodes either implanted or positioned external to the brainmay be used to stimulate or record or both stimulate and record anevoked neural response. In some embodiments, a combination of bothmicroelectrode and macroelectrodes may be used in any foreseeable manner

In a further application of the embodiments of the present inventionERNA measurements may be recorded and tracked over time to monitor theprogression or remission of a disease or syndrome, or used as adiagnostic tool (e.g. to classify the patient's neurological condition).Such embodiments may also be used to provide medical alerts to thepatient, a caregiver or a clinician in the event that the patient'sstate (as determined by ERNA) deteriorates towards an undesirable orcritical state (e.g. a Parkinsonian crisis).

In yet another application, ERNA may be used to monitor the effects ofmedication over time, including the effects of adjusting medicationdoses, etc. Such an embodiment may also be used to provide medicationalerts to the patient to remind them when a dose is required or when adose has been skipped. Tracking medication effects with ERNA may alsoprovide clinicians with information regarding whether medication isbeing taken as prescribed or whether medication is becoming lesseffective and requires dosing adjustment.

In any of the embodiments described herein, the patient may be awake orunder general anaesthetic. As discussed above with reference to FIGS. 27to 43, the inventors determined that ERNA remains present in patientsunder general anaesthetic and thus ERNA can be used during surgicalprocedures in which patients are under general anaesthetic. Moreover,since various properties of ERNA change under general anaesthetic, suchproperties may be used to determine the effect of general anaesthetic onERNA and therapeutic stimulation. Further, by comparing ERNA of an awakepatient to the same patient during anaesthetic induction andmaintenance, ERNA may provide a supportive indication of a patient'sconsciousness which may be beneficial in general anaesthesia generally.

General anaesthesia may be induced in any manner known in the art.Examples of intravenous induction agents that may be used to inducegeneral anaesthetic include propofol, sodium thiopental, etomidate,methohexital, and ketamine An example of inhalational induction agentthat may be used to induce general anaesthesia is sevoflurane.

General anaesthesia may be maintained in any manner known in the art,either through inhalation, intravenously or a combination thereof.Examples of suitable inhalation anaesthetics include isoflurane,sevoflurane, desflurane, methoxyflurane, halothane, nitrous oxide andxenon. Other inhalation anaesthetics which may be suitable includechloroethane (ethyl chloride), chloroform, cryofluorane, cyclopropane,diethyl ether, enflurane, ethylene, fluroxene, methoxypropane,trichloroethylene, and vinyl ether. Inhaled agents may be supplementedby intravenous anaesthetics, such as opioids (e.g. fentanyl or afentanyl derivative such as remifentanyl) and/or sedatives (such aspropofol or benzodiazepines, e.g. midazolam) and/or barbiturates (suchas thiopental).

Further Analysis of ERNA and Explanation of Results DBS Evokes ResonantNeural Activity

The neural activity resulting from DBS pulses was investigated todetermine if there were evoked responses that could feasibly be used asa biomarker. To preserve evoked activity we used a wide recordingbandwidth, as well as symmetric biphasic pulses for stimulation, ratherthan conventional asymmetric pulses with a very long second phase, tominimize the temporal duration of stimulation artifacts.

Recordings were made from DBS electrodes immediately following theirimplantation in the STN of patients with PD who were still awake on theoperating table, as PD is the predominant application for DBS.Furthermore, the STN's roles in regulation of motor, limbic, andassociative function make it a neural target relevant to a number ofdifferent applications, including DBS treatment of dystonia, essentialtremor, epilepsy, and obsessive-compulsive disorder.

It was found that STN-DBS evokes a large peak typically around 4 msafter each pulse. By examining the activity following the last pulseprior to cessation of DBS it was discovered that this peak is the firstin a series with progressively decreasing amplitude. As this responsehas a form that resembles a decaying oscillation, we describe it asevoked resonant neural activity (ERNA).

To further investigate ERNA, we temporally patterned standard 130 Hz DBSto allow multiple peaks to be observed. We employed two novel patterns:skipping one pulse every second, and applying a burst of ten pulsesevery second. The ‘skipped-pulse’ pattern was anticipated to havecomparable therapeutic effects to standard 130 Hz DBS, as it causes onlya 0.77% reduction in the total number of pulses delivered over time. Incontrast, the ‘burst’ pattern was anticipated to have minimaltherapeutic effects relative to continuous DBS, as only 7.7% of thepulses are delivered, making it a useful probe for investigatingactivity in the absence of therapy. The evoked responses tend toincrease in amplitude and sharpen across the consecutive pulses of aburst, and reach a steady state for longer duration stimuli.

We applied the burst stimulus to the STN of 12 PD patients (n=23hemispheres) undergoing DBS implantation surgery and observed ERNA ofsimilar morphology in all cases, indicating it is a robust and reliablesignal that can be measured across the patient population. As a controlto ensure that ERNA was not a specious artifact, we also applied theburst stimulus to 3 Essential Tremor patients (n=6 hemispheres) withelectrodes implanted in the posterior subthalamic area (PSA), a whitematter region medial to the STN. ERNA was not observed in the PSA,suggesting it is an electrophysiological response localizable to theSTN.

ERNA is Localizable to the STN

To establish that ERNA varies with electrode position relative to theSTN, we consecutively applied 10 s of burst stimulation to each of thefour DBS electrodes whilst recording from the three unstimulatedelectrodes. The DBS implantation surgery aimed to position two of thefour electrodes within the STN, with one electrode in the dorsal STNwhere DBS usually has greatest benefit and another in the ventral STN.This variance in electrode location facilitated comparison of ERNAresponses from different regions of the STN with those outside of thenuclei. In 8 STN-PD patients (n=16 hemispheres), we found that both ERNAamplitude and morphology varied depending on the stimulating andrecording electrode positions. FIG. 14 shows exemplar ERNA from the lastpulse of each burst in one hemisphere, with the responses with thelargest amplitude and most apparent decaying oscillation morphologyoccurring at the two middle electrodes in the target STN position. As acontrol, we also applied stimulation to two Essential Tremor patients(n=4 hemispheres) using an implantation trajectory intended to positiondistal electrodes within the PSA and proximal electrodes in the ventralintermediate nucleus of the thalamus, another target for tremor that haspreviously been shown not to elicit evoked activity beyond ˜2 ms.

As variation in ERNA amplitude was the most apparent feature, we used itfor further analysis. As not all recordings were in STN and containeddistinct resonant activity, to quantify ERNA amplitude we calculated theroot mean square (RMS) voltage over 4-20 ms. To estimate implantedelectrode positions relative to the STN, 3D reconstructions (FIG. 22)were generated using post-operative CT scans merged with pre-operativeMRI (FIG. 23). Electrodes were classified as being either superior to,inferior to, or within the STN, based on blinded measurements relativeto the red nucleus. Within-STN electrodes were then further classifiedto be either dorsal or ventral.

ERNA amplitude varied significantly with electrode position(Kruskal-Wallis, H(4)=45.73, p<0.001), with only the inferior electrodesnot significantly different from the PSA region (p=0.370) (FIG. 24).Although dorsal electrodes tended to be higher than ventral andsuperior, they were not significantly different in amplitude from eachother. To account for disparity in amplitude across patients due tovariation in electrode positioning in the medial-lateral andposterior-anterior planes and underlying differences in patientphysiology, we re-analyzed recordings from the STN-DBS electrodes afternormalizing responses to the total ERNA amplitude across eachhemisphere. After normalization, post hoc comparisons revealed asignificant difference in amplitude between dorsal and ventral STN(Kruskal-Wallis, H(3)=14.94, p=0.002; Dunn's method post hoc, dorsal vsventral: p=0.043, dorsal vs superior: p=0.081, dorsal vs inferior:p=0.002).

These results show that ERNA is localizable to, and varies across, theSTN, establishing its utility as a feedback signal for guiding electrodeimplantation to the most beneficial sites for stimulation. Furthermore,whilst variation in amplitude was the most apparent feature, other ERNAproperties, such as frequency, latency, and rate of change, also havepotential utility in discriminating STN regions.

ERNA is Modulated By DBS

To investigate whether ERNA was modulated by therapeutically effectiveDBS, we applied skipped-pulse stimuli of progressively increasingcurrent amplitude (range 0.67-3.38 mA) in blocks of 60-90 s to 10 STN-PDpatients (n=19 hemispheres). In general, it was found that the secondand subsequent peaks in ERNA were consistently observed toasymptotically increase in latency and spread further apart over timeand as stimulation amplitudes increased, consistent with a decrease inthe frequency of the resonant activity (FIGS. 5, 6, 21 a to 21 e). Inmany cases, the latency of the first peak also increased, although thischange was not consistent across all recordings. The amplitude of thepeaks was also generally observed to vary, often being greater at thebeginning of each stimulation block and then gradually diminishing.

To quantify these effects, we calculated the inverse of the differencein latency between the first and second peaks as a representativemeasure of ERNA frequency. We also calculated the amplitude differencebetween the first peak and the first trough as a representative measureof ERNA amplitude. We then used averages of the 45-60 s period of eachcondition as estimates of asymptotic ERNA values for analysis.

ERNA frequency significantly decreased across conditions (1-way RepeatedMeasures (RM) ANOVA, F(4.94)=45.79, p<0.001). Post hoc comparisons(Holm-Sidak) showed that ERNA frequency significantly decreased witheach increasing step of DBS amplitude (FIG. 25A), except from 2.25 mA to3.38 mA (p=0.074). The median frequency was 256 Hz at 3.38 mA,approximately two times the stimulation rate of 130 Hz. It has beenproposed that STN-DBS could act by creating a pacing effect within theglobus pallidus interna at two times the stimulation rate, due to theimmediate excitation of STN axons and inhibition/recovery time course ofSTN soma.

ERNA amplitude was also significantly different across conditions(Friedman, x²(4)=41.31, p<0.001). Tukey test post hoc comparisonsindicated that ERNA amplitude initially increased with DBS amplitude andthen plateaued at levels above 1.5 mA (FIG. 25B). While these effectsmay be related to the therapeutic effects of DBS, they may alternativelyor additionally be due to saturation of neural firing in the STN. Due tothis, we subsequently focused on ERNA frequency for correlation withtherapeutic effects.

ERNA Correlates with Therapeutic Effects

The clinical efficacy of stimulation was confirmed by rating limbbradykinesia and rigidity according to the Unified Parkinson's DiseaseRating Scale (UPDRS; items 22 and 23) immediately prior to stimulationand after 60 s at 2.25 mA. Both clinical signs improved significantly at2.25 mA indicating that DBS was therapeutic (Wilcoxon Signed Rank,bradykinesia: Z=−3.62, p<0.001, rigidity: Z=−3.70, p<0.001).

However, time constraints precluded clinical examinations with each stepin stimulation intensity. Therefore, to correlate ERNA modulation withpatient state, we used beta-band (13-30 Hz) spontaneous LFP activity.Excessive synchronization of oscillations within the beta band has beenstrongly implicated in the pathophysiology of PD and its suppression hasbeen correlated with improvement in movement impairments of bradykinesiaand rigidity.

Using short-time Fourier transforms we calculated ‘relative beta’, theRMS amplitude within the 13-30 Hz band divided by that within 5-45 Hz,as a representative measure of beta activity. We then averaged acrossthe 45-60 s period of each stimulation amplitude condition and foundrelative beta to significantly vary (1-way RM ANOVA, F(4.89)=18.11,p<0.001). Post hoc tests (Holm-Sidak) showed significant suppression at3.38 mA compared to all other conditions and at 2.25 mA compared to 0.67and 1 mA (FIG. 25C). These results are consistent with previous studiesshowing that beta activity suppression by DBS correlates withimprovement in clinical signs, and confirm that stimulation wastherapeutically effective at and above 2.25 mA.

To further correlate ERNA frequency with beta activity, and thustherapeutic efficacy, we compared average values for 15 snon-overlapping blocks across each condition (FIG. 25B). ERNA frequencywas significantly correlated with relative beta (Pearson product moment,p=0.601, n=90, p<0.001).

These results indicate that ERNA is a clinically relevant biomarker.Furthermore, its large amplitude, ranging from 20 μVp-p to 681 μVp-p(median 146 μVp-p), is orders of magnitude larger than spontaneous betaLFP activity, whose absolute values ranged from 0.9 to 12.5 μVRMS(median 2.2 μVRMS). The robustness of ERNA and its distinct andgradually modulated morphology (FIGS. 5, 6, 7, 21) contrast with theinherent variability in beta-band activity across patients and noisybursting on-off nature of the beta-band signal. ERNA is therefore a moretractable signal to use with a fully-implantable DBS device compared tonoisy, low-amplitude LFP measures.

ERNA Modulation Washes Out Following DBS

Immediately before and after the therapeutic skipped-pulse stimulationwe also applied 60 s of burst stimulation (hereafter referred to as pre-and post-DBS conditions), in order to monitor changes in activity astherapeutic effects washed out.

Generally, ERNA remained relatively stable pre-DBS, indicating themodulatory effects of burst stimulation were minimal. However,immediately post-DBS, ERNA peaks occurred at longer latencies beforegradually returning towards their pre-DBS state. To quantify theseeffects, we averaged post-DBS ERNA frequency and amplitude over 15 snon-overlapping blocks and compared them to the last 15 s pre-DBS. Overall hemispheres tested (n=19), differences were found in ERNA frequency(Friedman, χ²(4)=70.23, p<0.001), with frequencies at all time pointssignificantly reduced compared to the pre-DBS frequency except for thefinal 45-60 s block (Tukey, p=0.73) (FIG. 26A). ERNA amplitude alsosignificantly varied across the time points (Friedman, χ²(4)=31.37,p<0.001), with differences between amplitudes at post-DBS time pointsindicating a washout of amplitude suppression caused by therapeuticstimulation (FIG. 26B). As the burst stimulus applied was constantacross the pre- and post-DBS conditions, the variation observed in ERNAfrequency and amplitude can be directly attributed to changes in thestate of STN neural circuits as DBS effects washed out. Therapeuticallyeffective DBS therefore modulates both ERNA frequency and amplitude,indicating ERNA has multiple properties that can feasibly be used asbiomarkers and as tools for probing mechanisms of action.

We then assessed relative beta activity pre- and post-DBS and found itto be significantly different across time points (Friedman, χ²(4)=24.55,p<0.001). Consistent with previous reports, relative beta wassignificantly decreased immediately post-DBS and washed out to pre-DBSlevels after 30 s (FIG. 26C). Supporting the skipped-pulse results, ERNAfrequency was significantly correlated with relative beta pre- andpost-DBS (Pearson product moment, ρ=0.407, n=152, p<0.001). ERNAamplitude was also correlated with relative beta (Pearson productmoment, ρ=0.373, n=152, p<0.001), suggesting it too may have clinicaland mechanistic relevance.

We also analyzed spontaneous LFP activity in the high frequencyoscillation (HFO) band (200-400 Hz), which overlaps with the observedERNA frequencies. Changes in the HFO band have been correlated withmotor state and effective pharmacological therapy, particularly inconjunction with beta activity, and have been implicated in themechanisms of action of DBS. Concurrent ERNA and HFO analysis wasenabled by the use of burst stimulation, as data could be segmented toonly include activity between bursts, thereby providing LFP epochs thatwere free of stimulation artifacts that can otherwise corrupt the HFOband.

As the HFO activity was generally characterized by a broadband peak infrequency, we calculated multitaper spectral estimates and thendetermined the frequency and amplitude of the peak occurring between200-400 Hz. Comparing averages across 15 s non-overlapping blocks (FIG.26D), we found HFO peak frequency to be significantly decreased post-DBS(Friedman, χ²(4)=45.18, p<0.001), until the final 45-60 s block (Tukey,p=0.077). This washout trend matches that for ERNA frequency, albeit ata lower frequency, with a significant correlation between the two(Pearson product moment, ρ=0.546, n=152, p<0.001). The median HFO peakfrequency immediately post-DBS was 253 Hz, comparable to the median ERNAfrequency of the therapeutic 3.38 mA condition (256 Hz), suggesting HFOactivity occurs at the same frequency as ERNA during the more continuousskipped-pulse stimulation.

No significant differences were found in HFO peak amplitude (Friedman,χ²(4)=2.11, p=0.72), although it did significantly correlate with ERNAamplitude (Pearson product moment, ρ=0.429, n=152). It is likely thatthe very small amplitude (<1 μV) of HFO peaks resulted in any modulatoryeffects being obscured by noise in the recordings.

It will be appreciated by persons skilled in the art that numerousvariations and/or modifications may be made to the above-describedembodiments, without departing from the broad general scope of thepresent disclosure. The present embodiments are, therefore, to beconsidered in all respects as illustrative and not restrictive.

There follows a list of numbered clauses defining particular embodimentsof the disclosure. Where a numbered clause refers to an earlier numberedclause then those clauses may be considered in combination.

-   1. A method of monitoring neural activity responsive to a stimulus    in a brain of a subject, the method comprising:    -   a. inducing general anaesthesia in the subject;    -   b. applying the stimulus to one or more of at least one        electrode implanted in a target neural structure of the brain;    -   c. detecting a resonant response from the target neural        structure evoked by the stimulus at one or more of the at least        one electrode in or near the target neural structure of the        brain; and    -   d. determining one or more waveform characteristics of the        detected resonant response.-   2. A method of monitoring neural activity responsive to a stimulus    in a brain of a subject under general anaesthetic, the method    comprising:    -   a. applying the stimulus to one or more of at least one        electrode implanted in a target neural structure of the brain;    -   b. detecting a resonant response from the target neural        structure evoked by the stimulus at one or more of the at least        one electrode in or near the target neural structure of the        brain; and    -   c. determining one or more waveform characteristics of the        detected resonant response.-   3. The method of clauses 1 or 2, wherein the one or more waveform    characteristics are determined based on at least part of a second or    subsequent cycle in the detected resonant response.-   4. The method of any one of clauses 1 to 3, wherein the one or more    waveform characteristics comprises one or more of the following:    -   a) a frequency of the resonant response;    -   b) a temporal envelope of the resonant response;    -   c) an amplitude of the resonant response;    -   d) a fine structure of the resonant response;    -   e) a rate of decay of the resonant response;    -   f) a delay between the onset of the stimulus and the onset of a        temporal feature of the resonant response;    -   g) a duration between two peaks in the resonant response.-   5. The method of any one of the preceding clauses, wherein the    stimulus comprises a plurality of pulses.-   6. The method of any one of the preceding clauses, wherein    determining the one or more waveform characteristics comprises    comparing a first characteristic over two or more cycles of the    detected resonant response.-   7. The method of clause 6, wherein the step of determining the one    or more waveform characteristics comprises determining a change of    the first characteristic over the two or more cycles.-   8. The method of clauses 6 or 7, wherein the step of determining the    one or more waveform characteristics comprises determining a rate of    change of the first characteristic over the two or more cycles.-   9. The method of any one of the preceding clauses, wherein the    resonant response comprises a plurality of resonant components.-   10. The method of any one of the preceding clauses, wherein one or    more of the plurality of resonant components is from a neural    structure different from the target neural structure.-   11. The method of clause 8, further comprising adjusting the    location of one or more of the at least one electrodes based on the    one or more determined waveform characteristics.-   12. The method of any preceding clauses, further comprising:    -   adapting the stimulus based on the one or more determined        waveform characteristics of the resonant response.-   13. The method of clause 12, wherein the adapting comprises    adjusting one or more of the frequency, amplitude, pulse-width, net    charge, electrode configuration, or morphology of the stimulus.-   14. The method of clauses 12 or 13, further comprising:    -   correlating the detected resonant response with a template        resonant response; and    -   adapting the stimulus based on the correlation.-   15. The method of any one of any one of clauses 12 to 14, further    comprising:    -   correlating the one or more determined waveform characteristics        with one or more predetermined threshold values; and    -   adapting the stimulus based on the correlation.-   16. The method of any one of the preceding clauses, wherein the    stimulus is non-therapeutic or therapeutic.-   17. The method of any one of the preceding clauses, wherein the    stimulus comprises a patterned signal comprising a plurality of    bursts separated by a first time period, each burst comprising a    plurality of pulses separated by a second time period, wherein the    first time period is greater than the second time period and wherein    the detecting is performed during one or more of the first time    periods.-   18. The method of clause 17, wherein the plurality of pulses within    at least one of the bursts have different amplitudes.-   19. The method of clause 18, wherein the different amplitudes are    selected to produce a ramp in amplitude of sequential pulses in the    at least one of the bursts.-   20. The method of any one of clauses 17 to 19, wherein the final    pulse in each of the plurality of bursts is substantially identical.-   21. The method of any one of clauses 17 to 20, wherein during the    first time period the stimulus comprises a continuous therapeutic    stimulus.-   22. The method of clause 21, wherein the frequency of the stimulus    during the first time period is greater than the frequency of the    stimulus during the second time period.-   23. The method of any one of the preceding clauses, further    comprising:    -   applying a second stimulus to a target neural structure in the        brain;    -   detecting a second resonant response from the target neural        structure evoked by the second stimulus at one or more of the at        least one electrode implanted in or near the target neural        structure;    -   determining one or more second waveform characteristics of the        detected second resonant response.-   24. The method of clause 23, further comprising:    -   determining the effect of a therapy provided to the patient        based on the one or more first waveform characteristics and the        one or more second waveform characteristics.-   25. The method of any one of clauses 23 to 24, wherein the at least    one electrode comprises two or more electrodes located within    different neural structures in the brain.-   26. The method of clauses 25, wherein the at least one electrode    comprises two or more electrodes located within different    hemispheres of the brain.-   27. The method of any one of the preceding clauses, further    comprising:    -   determining whether one or more of the at least one electrode is        positioned in the target neural network based on the detected        resonant response.-   28. The method of clause 27, further comprising moving one or more    of the first electrode and the second electrode based on the    detected resonant response.-   29. The method of any of the preceding clauses, further comprising:    -   repeating the steps of applying the stimulus, detecting a        resonant response and determining one or more waveform        characteristics of the detected resonant response.-   30. The method of clause 29, further comprising comparing a common    waveform characteristic between two or more detected resonant    responses.-   31. The method of clauses 29 or 30, further comprising comparing a    degree of change of a common characteristic between two or more    detected resonant responses.-   32. The method of any one of clauses 29 to 31, further comprising    determining a rate of change of a common characteristic between two    or more detected resonant responses.-   33. The method of any one of clauses 30 to 32, wherein the steps of    applying the stimulus, detecting a resonant response and determining    one or more waveform characteristics of the detected resonant    response are repeated until it is determined that one or more of the    at least one electrode is positioned in the target neural structure.-   34. The method of any one of the preceding clauses, further    comprising:    -   selecting one or more of the at least one electrode to use for        therapeutic stimulation of the target neural structure based on        the one or more waveform characteristics; and    -   applying a therapeutic stimulus to the target neural structure        via the selected one or more of the at least one electrode.-   35. The method of clause 29, further comprising:    -   inserting the at least one electrode into the brain along a        predefined trajectory;    -   wherein steps of applying the stimulus, detecting a resonant        response and determining one or more waveform characteristics of        the detected resonant response are repeated while the at least        one electrode is being inserted to generate a profile of        resonant responses with respect to the predefined trajectory and        the target neural structure.-   36. The method of clause 35, wherein the profile of resonant    responses is used to determine a position of the one or more    electrodes relative to the target neural structure.-   37. The method of clause 29, wherein the at least one electrode    comprises a plurality of electrodes, and wherein the steps of    applying the stimulus, detecting a resonant response and determining    one or more waveform characteristics of the detected resonant    response are repeated using different combinations of the at least    one electrode to generate a profile of resonant responses.-   38. The method of clauses 36 or 37, further comprising:    -   selecting one or more of the at least one electrode based on the        profile of neural responses; and    -   applying a therapeutic stimulus to the selected one or more of        the at least one electrode.-   39. The method of clause 38, wherein the selected one or more of the    at least one electrode comprises a plurality of electrodes.-   40. The method of any one of the preceding clauses, wherein the one    or more of the at least one electrode used to apply the stimulus    comprises at least two electrodes and/or wherein the one or more of    the at least one electrode used to detect the resonant response    comprises at least two electrodes.-   41. The method of any one of the preceding clauses, wherein the    neural target structure is part of the cortico-basal    ganglia-thalamocortical circuit.-   42. The method of any one of the preceding clauses, wherein the    neural target structure is the subthalamic nucleus, globus pallidus    interna, substantia nigra pars reticulata, pedunculopontine nucleus.-   43. A method of monitoring neural activity in a brain of a subject    under general anaesthetic responsive to a stimulus, the method    comprising:    -   a. applying the stimulus to a target neural structure in the        brain; and    -   b. detecting a neural response evoked by the stimulus at an        electrode implanted in or near the target neural structure,    -   wherein the stimulus comprises a patterned signal comprising a        plurality of bursts separated by a first time period, each burst        comprising a plurality of pulses separated by a second time        period, wherein the first time period is greater than the second        time period and wherein the detecting is performed during one or        more of the first time periods.-   44. A method of monitoring neural activity in a brain of a subject    responsive to a stimulus, the method comprising:    -   a. inducing general anaesthesia in the patient;    -   b. applying the stimulus to a target neural structure in the        brain; and    -   c. detecting a neural response evoked by the stimulus at an        electrode implanted in or near the target neural structure,    -   wherein the stimulus comprises a patterned signal comprising a        plurality of bursts separated by a first time period, each burst        comprising a plurality of pulses separated by a second time        period, wherein the first time period is greater than the second        time period and wherein the detecting is performed during one or        more of the first time periods.-   45. The method of clauses 43 or 44, wherein the first time period is    greater than or equal to the second time period.-   46. The method of any one of clauses 43 to 45, wherein the stimulus    is biphasic.-   47. The method of any one of clauses 43 to 46, wherein the plurality    of pulses within a burst have different amplitudes.-   48. The method of clause 47, wherein the different amplitudes are    selected to produce a ramp.-   49. The method of any one of clauses 43 to 48, wherein the final    pulse in each of the plurality of bursts is substantially identical.-   50. The method of any one of clauses 43 to 49, wherein the stimulus    is patterned to be non-therapeutic or therapeutic.-   51. The method of any one of the preceding clauses, wherein general    anaesthesia in the subject is induced using an agent selected from    propofol, sodium thiopental, etomidate, methohexital, ketamine, and    sevoflurane.-   52. The method of any one of the preceding clauses, wherein general    anaesthesia in the subject is maintained using an agent selected    from soflurane, sevoflurane, desflurane, methoxyflurane, halothane,    nitrous oxide, and xenon.-   53. The method of any one of the preceding clauses, wherein general    anaesthesia in the subject is maintained using fentanyl derivative,    a barbiturate, or benzodiazepines.-   54. The method of any one of the preceding clauses, wherein general    anaesthesia in the subject is induced using propofol and maintained    using a combination of sevoflurane and remifentanyl.

1. A method of monitoring neural activity responsive to a stimulus in abrain of a subject, the method comprising: a. inducing generalanaesthesia in the subject; b. applying the stimulus to one or more ofat least one electrode implanted in a target neural structure of thebrain; c. detecting a resonant response from the target neural structureevoked by the stimulus at one or more of the at least one electrode inor near the target neural structure of the brain; and d. determining oneor more waveform characteristics of the detected resonant response.
 2. Amethod of monitoring neural activity responsive to a stimulus in a brainof a subject under general anaesthetic, the method comprising: a.applying the stimulus to one or more of at least one electrode implantedin a target neural structure of the brain; b. detecting a resonantresponse from the target neural structure evoked by the stimulus at oneor more of the at least one electrode in or near the target neuralstructure of the brain; and c. determining one or more waveformcharacteristics of the detected resonant response.
 3. The method ofclaims 1 or 2, wherein the one or more waveform characteristics aredetermined based on at least part of a second or subsequent cycle in thedetected resonant response.
 4. The method of any one of claims 1 to 3,wherein the one or more waveform characteristics comprises one or moreof the following: a) a frequency of the resonant response; b) a temporalenvelope of the resonant response; c) an amplitude of the resonantresponse; d) a fine structure of the resonant response; e) a rate ofdecay of the resonant response; f) a delay between the onset of thestimulus and the onset of a temporal feature of the resonant response;g) a time elapsed between two peaks of the resonant response.
 5. Themethod of any preceding claims, further comprising: adapting thestimulus based on the one or more determined waveform characteristics ofthe resonant response.
 6. The method of claim 5, wherein the stimulus isadapted based on the time elapsed between adjacent peaks in the resonantresponse.
 7. The method of claim 6, wherein the stimulus is adapted ifthe time elapsed between two adjacent peaks in the resonant response isless than a first predetermined time period associated with alleviationof movement symptoms in the patient.
 8. The method of any one of thepreceding claims, wherein the stimulus comprises a patterned signalcomprising a plurality of bursts separated by a first time period, eachburst comprising a plurality of pulses separated by a second timeperiod, wherein the first time period is greater than the second timeperiod and wherein the detecting is performed during one or more of thefirst time periods.
 9. The method of any one of the preceding claims,further comprising: applying a second stimulus to a target neuralstructure in the brain; detecting a second resonant response from thetarget neural structure evoked by the second stimulus at one or more ofthe at least one electrode implanted in or near the target neuralstructure; determining one or more second waveform characteristics ofthe detected second resonant response.
 10. The method of any one of thepreceding claims, further comprising: determining whether one or more ofthe at least one electrode is positioned in the target neural networkbased on the detected resonant response.
 11. The method of any of thepreceding claims, further comprising: repeating the steps of applyingthe stimulus, detecting a resonant response and determining one or morewaveform characteristics of the detected resonant response.
 12. Themethod of any one of the preceding claims, further comprising: selectingone or more of the at least one electrode to use for therapeuticstimulation of the target neural structure based on the one or morewaveform characteristics; and applying a therapeutic stimulus to thetarget neural structure via the selected one or more of the at least oneelectrode.
 13. The method of claim 12, wherein the at least oneelectrode comprises a plurality of electrodes, and wherein the steps ofapplying the stimulus, detecting a resonant response and determining oneor more waveform characteristics of the detected resonant response arerepeated using different combinations of the at least one electrode togenerate a profile of resonant responses.
 14. The method of any one ofthe preceding claims, wherein the one or more of the at least oneelectrode used to apply the stimulus comprises at least two electrodesand/or wherein the one or more of the at least one electrode used todetect the resonant response comprises at least two electrodes.
 15. Themethod of any one of the preceding claims, wherein the neural targetstructure is part of the cortico-basal ganglia-thalamocortical circuit.16. The method of any one of the preceding claims, wherein the neuraltarget structure is the subthalamic nucleus, globus pallidus interna,substantia nigra pars reticulata, pedunculopontine nucleus.
 17. A methodof monitoring neural activity in a brain of a subject under generalanaesthetic responsive to a stimulus, the method comprising: a. applyingthe stimulus to a target neural structure in the brain; and b. detectinga neural response evoked by the stimulus at an electrode implanted in ornear the target neural structure, wherein the stimulus comprises apatterned signal comprising a plurality of bursts separated by a firsttime period, each burst comprising a plurality of pulses separated by asecond time period, wherein the first time period is greater than thesecond time period and wherein the detecting is performed during one ormore of the first time periods.
 18. A method of monitoring neuralactivity in a brain of a subject responsive to a stimulus, the methodcomprising: a. inducing general anaesthesia in the patient; b. applyingthe stimulus to a target neural structure in the brain; and c. detectinga neural response evoked by the stimulus at an electrode implanted in ornear the target neural structure, wherein the stimulus comprises apatterned signal comprising a plurality of bursts separated by a firsttime period, each burst comprising a plurality of pulses separated by asecond time period, wherein the first time period is greater than thesecond time period and wherein the detecting is performed during one ormore of the first time periods.
 19. The method of claims 17 or 18,wherein the first time period is greater than or equal to the secondtime period.
 20. The method of any one of claims 17 to 19, wherein thefinal pulse in each of the plurality of bursts is substantiallyidentical.
 21. The method of any one of claims 17 to 20, wherein generalanaesthesia in the subject is induced using an agent selected frompropofol, sodium thiopental, etomidate, methohexital, ketamine, andsevoflurane.
 22. The method of any one of claims 17 to 20, whereingeneral anaesthesia in the subject is induced using propofol andmaintained using a combination of sevoflurane and remifentanyl.
 23. Themethod of any one of claims 17 to 22, wherein general anaesthesia in thesubject is maintained using an agent selected from soflurane,sevoflurane, desflurane, methoxyflurane, halothane, nitrous oxide, andxenon.
 24. The method of any one of claims 17 to 22, wherein generalanaesthesia in the subject is maintained using fentanyl derivative, abarbiturate, or benzodiazepines.